After a bit of a hiatus from the blog – thanks to our ambitious summer travel schedule – it’s time for another post. Over the years, I’ve gotten a lot of questions about the Shiller CAPE Ratio and if it’s still relevant. If you’re a regular reader of my blog, you’ll likely be familiar with the CAPE concept, but just as a refresher, Prof. Robert Shiller, economist and Nobel Laureate, came up with the cool idea of calculating a Price-Earnings (PE) ratio based not just on 1-year trailing earnings, which can be very volatile, but on a longer-term average to iron out the corporate earnings fluctuations over the business cycle. Hence the name **Cyclically-Adjusted** Price Earnings (CAPE) Ratio. If we use a 10-year moving average of inflation-adjusted earnings as the denominator in the PE ratio, we get a measure of market valuations that’s more informative in many instances. For example, historically the CAPE ratio has been significantly negatively correlated with subsequent equity returns. It’s not useful for the very short-term equity outlook, but over longer horizons, say 10+ years, the CAPE ratio has been highly informative. Especially retirees should take notice because your retirement success hinges a lot on those first 10 or so retirement years due to Sequence of Return Risk. In fact, all failures of the 4% Rule occurred when the CAPE was above 20! A high initial CAPE ratio signals that retirees should probably be more cautious with their withdrawal rate!

But the CAPE has been elevated for such a long time, people wonder if this measure is still relevant. In the comments section, people ask me all the time what kind of adjustments I would perform to “fix” the CAPE. Can we make the Shiller CAPE more comparable over time, to account for different corporate tax environments and stock buybacks and/or dividend payout ratios over the decades? Yes, I will present my ideas here today. And even better, I will post regular updates (potentially daily!) in my Google Drive for everyone to access for free.

So, what do I find? The adjustments certainly lower the CAPE, but don’t get your hopes too high. Even after the adjustments, the CAPE is still a bit elevated today! Let’s take a look at the details…

Before we even get started with the tax and dividend payout ratios, here are two additional and crucial adjustments I always like to perform when calculating the Shiller CAPE. I might have mentioned these adjustments in a previous post, but never delved much into the details. But today is a good excuse to do so…

First, Shiller operates with woefully outdated data, especially earnings data. That may not be too much of a problem in typical macroeconomic research projects studying many decades worth of data. But the average retiree likes to have a timely and accurate estimate of the CAPE Ratio. Below is a screenshot from the Shiller Excel Sheet posted on his website. I downloaded this file on October 3, 2022. The first thing we notice is that the data are crazy outdated. The rows only go to July 2022 and the index level not even the month-end but July 5, so almost 3 months outdated. Of course, we can still derive a pretty decent estimate of the October 3 Shiller CAPE. For example, if we use an SPX quote of 3678.43 (=index level as of 10/3/2022, market close) and we rescale the 28.90 CAPE to 28.90/3831.39*3678.43 we get a CAPE of 27.75. But that’s not really precise because the July 2022 CAPE ratio uses the average real earnings over the 120 months of July 2012 to June 2022. But for the October 2022 CAPE, we have to use October 2012 to September 2022 average real earnings. We are using 3 months of data we shouldn’t use and are missing 3 months worth of data that we should be using.

But the data lag problem is even worse. Shiller’s earnings data go only up to March 2022. So, even back in July, he was 3 months short of earnings data. So, we are inadvertently underestimating the “E” part of the CAPE calculation because we’re putting a weight of 1/117 instead of 1/120 on the (significantly lower) earnings numbers from ten years ago. And using Shiller’s data for an October 2022 CAPE ratio estimate we’re now missing 6 months’ worth of earnings data. Excuse me for being pedantic, but that’s not acceptable.

So, how do I deal with the missing data in the Shiller Sheet? The first problem is easy to solve: I simply download the additional SPX index data for the other months. But what about the earnings data? The problem is that even as of October 3, 2022, the earnings for Q2 are not 100% finalized. According to the index provider, DJ SP Global, that Q2 number is “only” 99.8% final, so there are still 0.2% of the index members that haven’t finalized their number (link to their Excel Sheet).

Well, 99.8% is obviously good enough. And remember, the 99.8% refers to the **current **quarter. Shiller uses the 4-quarter moving average, so the estimate for the annual trailing earnings per share (EPS) is really 99.95% finalized as of 10/3/2022. So, I can certainly use the $192.26 estimate for June 2022. (also notice that, just as a quick check, the 197.91 and 197.87 figures for 2022Q1 and 2021Q4 exactly match the Shiller numbers, so he’s getting his numbers from the same source.)

And while we’re at it, I am also using the subsequent earnings forecasts for Q3 as the September EPS number in my table. And just like Shiller, I linearly interpolate the EPS for the months in between. And I concede that these are only forecasts, and sure, the forecasts may be off. But not using the SP Global estimates and effectively using the average over the 114 past months as an estimate for the six missing months is also a forecast and likely one with an even greater error!

In any case, I wrote a little Python program to perform the Shiller CAPE calculations, but instead of using the outdated Shiller EPS data, I access the SP Global data and fill in the missing earnings data and use the earnings estimates of the index provider instead. See the output below:

One peculiar feature of the data displayed above is that I get different SPX index readings. That’s because Prof. Shiller uses **monthly average **index levels, while I am using the **month-end figure** (or the latest available in the current month). In fact, using the month-end index levels is the second change I like to make in the CAPE calculation. Just to be sure, there is no correct or incorrect way. For example, as a macroeconomist, you might indeed be more interested in the **average **valuation of the S&P 500 during the month of September 2022. However, if you’re a retiree and pondering about what’s the right withdrawal rate **today**, then you’d be better served using today’s S&P value and not a 31-day moving average. That’s because you will sell your equities at **today’s** price not an **average **price over the last month. So, with those two adjustments, the table below is a sample of the most recent CAPE calculations.

Notice how the estimates can be significantly different. For example, in April, my CAPE (31.94) is almost 6% below the Shiller CAPE (33.89). That’s because the index finished significantly below the monthly average. Differences like that will certainly have a meaningful impact on your CAPE-based withdrawal rate. You don’t want to be sloppy about that. Precision is important in retirement planning!

And I want to make one thing really clear: I’m not trying to ding Prof. Shiller’s methodology. It may be correct in another context. But for our specific application, using the most recent index value and padding the EPS data with the currently available estimates makes the most sense.

Sorry about the deep dive into the CAPE methodology. For the three to four readers that haven’t fallen asleep yet, let’s talk about the issues mentioned in the intro now. One criticism of the Shiller methodology is that the CAPE has been elevated for such a long time. It seems that a CAPE ratio in the high-20s in today’s market seems a lot more sustainable than in the 1920s or 30s. What could be responsible for this shift? I found an interesting post by a guy called Damien Klassen on a financial planner website that proposes adjustments for both corporate taxes and share buybacks. I liked the way he models the corporate tax adjustments and I will use his methodology one-for-one. But I will use a slightly different approach for the buybacks, more on that below.

First, why do we want to adjust for corporate taxes? Imagine there’s a corporation that generated (CPI-adjusted) pre-tax earnings of exactly $100 a year for the last 10 years. During the last five years, corporate taxes were 21%, and thus the corporation earned $79 after-tax. The five years before that, corporate taxes were 35% and the company earned $65. Your average 10-year rolling earnings were $72. But $72 is a really poor estimate for the earnings trend. Your tax rate today isn’t 28% but 21%. Thus, the Klassen adjustment takes all past earnings and divides them by 1.0 minus the **then**-prevailing tax rate to get a sense of the pre-tax earnings. And then you apply the **current **corporate tax rate to all past earnings. Klassen thus calculates the 10-year after-tax rolling earnings per share (EPS) as if today’s corporate tax rates had been in effect for the entire past 10 years. The reason for this adjustment is that it would take an entire 10 years for a tax cut like the 2018 corporate tax reduction (from 35% to 21%) to work itself through Shiller’s CAPE calculations. The Klassen adjustment applies the tax impact instantaneously, exactly when the tax cut happens.

Thus, whenever corporate tax rates have decreased, our adjustment will increase the rolling average EPS used in the denominator and thus lower the CAPE, increasing the valuation-based attractiveness of stocks. And by the way, if the corporate tax rate were to rise again, and there are some rumblings in Washington D.C. right now, then this effect reverses and the adjusted Shiller CAPE will look unattractive again.

The second adjustment has to do with **share buybacks. **Mr. Klassen doesn’t spend a lot of time explaining the rationale behind his adjustment. So here’s my take. Imagine we have two very similar corporations: Corporation A and Corporation B. They each have $1,000 of capital that generates $100 in CPI-adjusted profits every year for each corporation. They are also both valued at $1000. Imagine they each have 100 shares in circulation, valued at $10 a share.

Corporation A pays out all of its earnings as dividends, i.e., $1.00 per share. Corporation B retains all its earnings and simply buys back shares in the equity market. Thus, the investors in corporation B, in lieu of receiving a dividend, will see their share price increase by 10% every year. And if they want to get the same cash flow as the Corporation A shareholders they simply sell 10% of their shares every year. On average, people would have to do so anyway because of the buyback demand.

In a perfect world then, investors should be completely indifferent between the two corporations. You make 10% p.a. and people shouldn’t care if they get their 10% return through dividends or capital gains. Of course, in a slightly imperfect world, retail investors with taxable accounts might prefer corporation B because you can defer your capital gains taxes. But let’s abstract from that issue. A lot of retail money is in tax-deferred accounts and a lot of institutional investors (pension funds, endowments, sovereign wealth funds, etc.) don’t pay income taxes directly either; only the retirees that will eventually get the benefits will pay income taxes. In any case, we should agree that the equity return from investing in the two corporations will be identical in a perfect world and close to identical in the real world.

What would be the CAPE ratio of the two corporations? Corporation A had $1.00 earnings per share in each of the last 10 years. With a share price of $10.00, we get a CAPE of exactly 10. People might be tempted to argue that Corporation B has the same CAPE. But that’s incorrect! Recall that Corporation B has 100 shares now, but the share number has been declining by 10% every year. So, one year ago, we had 100/0.9=111.11 shares. Two years ago there are 100/0.9^2 shares=123.46 shares, and so on. Thus, earnings were only $0.39 a share at the beginning of the 10-year window and then grew by 10% each year to reach $1.00 in the current year, see the table below. Thus, the rolling 10-year average EPS in Corporation B was only about $0.65 vs. the $1.00 in the dividend-paying company.

This implies a CAPE of 15.35, more than 50% above the CAPE of the dividend payer. Thus, share buybacks would consistently hurt CAPE valuations relative to dividend payers. To adjust for this disadvantage, Klassen proposes to make an adjustment to the EPS to account for the changing number of shares. Specifically, he scales up the past EPS numbers to exactly undo the effect of the shrinking share base due to the buybacks. Basically, scale up corporation B’s EPS sequence [0.39,0.43,…,0.90,1.00] back to [1.00,…,1.00] to make it comparable to Corporation A.

I agree with Klassen’s general idea, but there are two problems with his approach: First, I don’t trust the share buyback data, certainly not the historical data. And second, not only buybacks, but **any **kind of reinvestment of retained earnings should trigger an adjustment in the CAPE. To illustrate this point, let me introduce Corporation C. It pays no dividend and it does not buy back shares either. Instead, it uses its corporate earnings to **grow its productive capital.** We could imagine that this corporation purchases more machines that will yield that same 10% return on equity. Or alternatively, this corporation might even purchase shares of the other two companies. In either case, if I assume again that Corporation C also has 100 shares outstanding and $10 in earnings in 2022, then the stats for Corporation C look as follows, see the table below. We get the same messed-up CAPE ratio, even though this company generates the exact same annual returns per share as the other two corporations:

Summary so far: an adjustment has to be made not just for buybacks but for **all **retained earnings, provided they are directed at investments that are at least as profitable as the return on equity (ROE) of the overall corporation. That certainly doesn’t have to be the case for all corporations. Some companies have a terrible record of investing – looking at you General Electric under Jeffrey Immelt. But for the economy as a whole, that should be a good assumption.

And you know what’s the advantage of taking into account all retained earnings? Data availability! Screw the whacky buyback data because we do have reliable earnings and dividends data. We can just calculate the reinvestment percentage equal to the earnings yield minus the dividend yield, create an EPS scaling factor equal to 1.0 in the current year and then compound the growth in that scaling factor from reinvested earnings going backward. If you’re interested, Klassen posts his Excel Sheet and he shows how he calculates this with the buyback percentages. I use the same methodology but I simply use the earnings minus dividend yield numbers instead of the buyback percentages.

So, with all those adjustments, what CAPE ratio do we get today, as of 10/3/2022, when I’m writing this? That’s in the table below. We go from a 26.59 CAPE without adjustments to 21.40. That’s a 20% drop in the CAPE Ratio. Quite meaningful. But keep in mind that even at that CAPE we’re significantly above historical average CAPE ratios (about 15). So, we’d still expect below-average returns going forward.

Here’s the same chart as in the blog post header again, the CAPE time series since 1925. The adjustments didn’t make a large difference in the 1920s and 1930s. From the early 40s to the mid-50s, the adjusted CAPE was even higher than the unadjusted one (due to a rise in corporate tax rates). Only in the mid-1980s did we really see the adjusted CAPE come down, as a result of both corporate tax rates as well as dividend payout ratios moving down.

And here’s a time series chart since 1970, when the adjustments are really the most noticeable. Instead of plotting the CAPE, though, I transform this into an earnings yield (one divided by the CAPE), so this would be a series with a positive correlation with future earnings.

There are meaningful differences. In the late-1980s the adjusted CAPE yield was about 2 percentage points higher. It didn’t make too much of a difference during the dot-com bubble and more recently we see an impact of about one percentage point. But of course, the CAPE adjustment can’t so easily explain away the crazy CAPE valuations we’ve had over the last two decades. Even with the adjustment, earnings yields are still low compared to historical ones. Indeed, looking at longer-term averages in the table below, we see that the average CAPE yield has been about 6.78% (roughly a CAPE of 15, the widely-cited historical average) over the last 100 or so years. The standard CAPE yield since 2000 has been only 3.87 (a CAPE average of about 26). Even with the adjustment, we can lift that most recent CAPE yield to only 4.55%. Still much lower than long-term averages. But keep in mind that a 0.67 percentage point (absolute) increase, is still a relative increase by more than one-sixth. For example, if someone wanted to tie his or her withdrawal rate to the CAPE, then the **withdrawal rate** may only go up by 0.67 percentage points, but the annual **withdrawal amounts** will rise by 17.37%. That can be tens of thousands of dollars annually!

Oh, and before I forget, I post my CAPE numbers, specifically, the entire time series since 1871, here on my Google Drive:

**https://drive.google.com/file/d/1ugtRN3TaAVwQi-20mjt4DctF-glppSMD/view?usp=sharing**

Please let me know if you have trouble accessing the file. As usual, you can view the file, but before you do edits, you’ll have to download it to your own computer and/or Google Drive. I will run this (almost) every weekday, so you should be able to get regular updates on the most recent CAPE estimates, both the standard CAPE.ERN.1 and the adjusted CAPE.ERN.2. And for fun, you can also monitor how hopelessly outdated the Shiller numbers are.

Someone in the comments section pointed out that Frank Vasquez from the “Risk Parity Radio Podcast” recently had an episode criticizing valuation in general and the CAPE ratio in particular. If you don’t want to listen to the whole thing, the relevant part starts at the 25:00 mark. The “definitive proof” he puts forward: The CAPE was high in 2011 and subsequent returns were high as well. One single counter-example!? Well, that’s not really proving anything. Even if he had found one single counter-example it would only weaken, not eliminate the case for the CAPE. But Frank’s argument is even worse! In fact, his precise example works **in favor of the CAPE ratio.** The 2011 CAPE earnings yield (using my new adjusted series) hovered around 4.6% and subsequent returns were almost 14% (Dec 2011 to Dec 2021). But guess what? Compared to the valuations prevailing during that time, say starting in 2000, we get a beautiful positive correlation between valuation and subsequent returns. 2011 had much more attractive valuations than 2000 or 2007, right before the respective bear markets starts. And 2011 had much better subsequent 10-year returns than 2000 or 2007. **Thanks, Frank, for providing more proof that valuations matter!**

Time to wrap up since we’re already pushing past 3,000 words. To sum up, we can easily fix Shiller’s data reporting lags and we can certainly apply some adjustments to the Shiller CAPE. But the measure remains solidly above its long-term average, even after the major drop this year. What does this all mean for retirees? Initially, I had planned to make this part 54 of my Safe Withdrawal Rate Series with additional calculations on how the different CAPE Ratio scenarios impact your retirement safe withdrawal rates, but I will defer that to another post, hopefully in the next one or two weeks. Stay tuned!

Last week we got the Q2 GDP numbers and the Bureau of Economic Analysis (BEA) confirmed that GDP has now declined for two consecutive quarters. What do I make of that? Are we in a recession now? Since several people asked me to comment on this issue, here are my thoughts…

In the United States, we use two different competing definitions of a recession:

- We’re in a recession if an independent panel of famous economics professors associated with the National Bureau of Economic Research (NBER) decides so.
- We’re in a recession if we experience two consecutive quarters of GDP declines.

Both definitions have their pros and cons. In academic circles, you’ll find more support for the first one. In Wall Street circles, most people follow the second one. And in political circles, people follow the definition that best suits their current needs, i.e., Democrats currently point out that because the NBER hasn’t called a recession, we can’t possibly be in a recession right now (false, because economic turning points are always backdated), while Republicans insist that the second definition is the only one we’ve ever used (also false).

The advantage of the 2-quarter negative growth definition is that you avoid the long delays when confirming the business cycle turning points. The first GDP estimates come out about four weeks after the end of the quarter (though they’d be subject to further revision). The simple two-quarter GDP definition is thus more useful for practitioners, i.e., folks on Wall Street. Academics, on the other hand, can be more “academic”; they can afford to wait a year or two to guarantee certainty about the business cycle turning points. As someone who’s worked in both academic and Wall Street circles, I can tell you that clocks run a bit slower in academia. I once submitted a paper to a journal in 2001 and it was published in 2006. Wall Street wants to move a bit quicker than that!

Waiting for the NBER to make their decision can be frustrating. Take, for example, the 2001 recession. The NBER didn’t announce the March 2001 recession start until November 2001. The timing is ironic because that month turned out to be the end of the recession. That’s like a pregnancy test where the result is available after the baby is born. And the November 2001 end of the recession wasn’t confirmed by the NBER until 2003. So, anyone who argued in the Summer of 2001 that there is no recession because the NBER hadn’t announced one yet, was wrong!

The 2001 recession was special in another way: That recession didn’t even satisfy the second criterion. In 2001, the first and third quarter GDP growth was negative, but the second quarter GDP number was ever so slightly positive. The same pattern, negative-positive-negative growth quarters, also occurred during the 1960-1961 recession. Also notice that the pandemic recession spanned only two months: March and April 2020. Just by dumb luck, the 2020 recession spanned two quarters and indeed produced the “magical” two consecutive quarters. Had the 2020 recession occurred just one month earlier or one month later, then the two recession months would have fallen into the same quarter. And we would have observed only one quarter of negative GDP growth, again falling short of the two consecutive quarters of decline criterion.

So, the two-consecutive quarters of negative GDP growth is certainly not a **necessary** condition for the NBER to eventually declare a recession. But is the second criterion a **sufficient** condition for the NBER to declare a recession? At least in recent history, there hasn’t been any 2-quarter contraction outside of an NBER recession.

In the rest of the post, let me try to look for indicators to support the two sides of the “recession or not” argument:

First, for a recession, the labor market is still too strong. Normally, we see an increase in the unemployment rate and a decline in payroll employment. This morning (August 5, 2022) we just got another Nonfarm Payroll Employment release from the Bureau of Labor Statistics (BLS), and payrolls grew by another strong rate of 528,000 in the month of July. The unemployment rate dropped another notch to 3.5%.

In fact, before the slower-moving monthly numbers display signs of weakness, we normally observe a marked uptick in the weekly unemployment claims, which regular readers of my blog will remember is my preferred labor market business cycle indicator. Sure, there is a bit of an increase, but neither the level nor the slope of the unemployment claims is screaming “recession” right now.

Second, some of the other indicators the NBER will closely watch are not looking too shabby either. Industrial Production expanded during the first five months of the year. True, in June we saw a slight decrease but this is a volatile series and we don’t normally call a recession every time this indicator sees a small month-over-month decline. But watch this series going forward. Economic weakness normally shows up in IP before you see a payroll drop. So another 1 or 2 months of IP decline would certainly set off my recession alarm bells!

Real Personal Income also still looks solid. The usual disclaimer applies, that there are many households still hurting from the pandemic and/or inflation, but the macro picture – aggregating over all households – still looks solid, which bodes well for consumption going forward.

My preferred manufacturing indicator is the Purchasing Managers Index (PMI), both the headline index and the “New Orders” component. Both indicators have indeed declined recently but they still look too strong for an outright recession. The headline (overall) PMI index stands at 53 in July, still solidly in the expanding region (above 50). The slightly more leading New Orders subcomponent indeed slipped below 50, indicating a slight contraction in business activity. But we’d occasionally see levels slightly below 50 even during economic expansions. I’d get worried if we fall below 45.

Also notice that financial markets have been holding up. True, the S&P 500 index dropped by more than 20% between January 3 and June 16 this year but has recovered about half of the loss since. We’re now only about 13% below the all-time-high (8/4/2022 S&P 500 close). And just to be sure, this doesn’t mean that we’re in a new Bull Market again. See my 2020 post about this topic!

Also, a reliable financial stress indicator is the interest rate spread that corporations must pay over and above safe government bonds. The OAS (option-adjusted spread) of High-Yield bonds spiked a little bit in June this year but has moderated again. What’s more, even that spike was nowhere near what we’ve observed in other recessions (2001, 2008-9, 2020). That little blip on the screen didn’t even come close to some of the other false alarms (1998 LTCM, 2011 downgrade, 2016 Fed scare) that never even came close to a full-blown recession.

But all that said, not everything looks rosy either. Next, let me make the pessimistic case…

Most prominently, the yield curve recently inverted again. As you remember from previous blog posts, this indicator is on the top of my list as one of the most reliable early warning signs of a slowdown. What makes me worried about the current yield curve today is that the 10-2 yield curve slope didn’t just dip below zero by a few basis points but by a full 37 basis points (August 3, 2022). The bond market tells us that after the Fed slashes the inflation dragon, it must subsequently lower interest rates again (and aggressively!) to deal with the ensuing recession. The 10-year yield has dropped from 3.49% (June 14) to now well under 3%. That’s not a good sign. I always say that the smartest people on Wall Street are the Fixed Income Folks. They seem to know something that the rest of us didn’t figure out yet!

Another concern: Can the Fed really accomplish its goal of reducing inflation with modest interest rate hikes? Maybe not. Thus, complacency about rate hikes is another risk factor. If you remember, the Federal Reserve rate hike forecast published in June stood at 3.4% and 3.8% by the end of 2022 and 2023, respectively (and then 2.5% long-term, which I interpret at December 2026 in the chart below). Since then, interest rate forecasts have come down from even these modest levels. Fed Funds Futures markets now stand at 3.0% for December 2023 ( as of 8/3/2022).

What’s the reason for everyone predicting that the Fed will take it easy with the rate hikes? There is mounting evidence that the July CPI numbers, to be published in mid-August will see a marked decline. But is that one-time decline enough for inflation pressures to miraculously reverse? Even if the Y/Y CPI reading drops from 9.1% to 8% or even 7%, that’s still unsustainably high. For as long as inflation is elevated, it’s much more likely that the FOMC will keep raising rates. At 50-75bps every meeting we’ll easily get well above the levels currently predicted by the interest rate forecasts.

As I wrote in my post a while ago, people at the Fed will probably breathe a sigh of relief if we entered a mild recession that will ease the price pressures sooner rather than later. That’s preferable to the Fed going into Paul-Volcker mode necessitating a positive real(!) Fed Funds rate, which would currently imply a nominal policy rate of, say, 12.1% if targeting a 3% real rate. That would do a trick on the economy!

Another issue that’s not fully appreciated is that the labor market, despite recent gains, is still massively underwater from the pandemic shock. In other words, people pointing to the healthy labor market say that the **trajectory** is fine. But the **level** is still severely depressed. More than two years into the economic recovery, nonfarm payrolls just passed their February 2020 peak. If we were to apply a 125,000 monthly trend job growth rate to keep up with population growth, after 2.5 years we’re still 3.75 million jobs underwater, relative to the trend growth path extrapolated forward from the February 2020 peak. So, maybe this could be the first recession where employment doesn’t drop or doesn’t drop much because employment never really **recovered** from the previous recession.

So, what’s my verdict? I’m more aligned with the NBER economists: It’s too early to tell. The economy doesn’t display the typical recession pattern yet, but not all is well in the macroeconomy. In other words, we appear to be in that limbo state where the economy certainly shows signs of weakening, but it’s too early to call an outright recession. Think of today’s economy as in the same condition as the stock market in the Spring of 2022. It was already down, but not enough to call it a bear market. It could have recovered again and it would have been a false alarm. But when the market finally hit the -20% mark, the Bear Market was called and its starting point was then **backdated(!) **to January 4, the day after the all-time high on January 3. So, people who point out that the NBER hasn’t declared an economic turning point yet shouldn’t pounce too aggressively on the crowd following that “naïve” 2-quarter negative GDP criterion. That criterion might turn out to be correct again, we just don’t know it yet!

*Title image by Markus Spiske from Pixabay*

Over the last few decades, we’ve become accustomed to a negative correlation between stocks and U.S. Treasury bonds. Bonds used to serve as a great diversifier against macroeconomic risk. Specifically, the last four downturns in 1991, 2001, 2007-2009, and 2020 were all so-called “demand-side” recessions where the drop in GDP went hand-in-hand with lower inflation because a drop in demand also lowered price pressures. The Federal Reserve then lowered interest rates, which lifted bonds. This helped tremendously with hedging against the sharp declines in your stock portfolio. And in the last two recessions, central banks even deployed asset purchase programs to further bolster the returns of long-duration nominal government bonds. Sweet!

Well, just when people start treating a statistical artifact as the next Law of Thermodynamics, the whole correlation collapses. Bonds got hammered in 2022, right around the time when stocks dropped! At one point, intermediate (10Y) Treasury bonds had a worse drawdown than even the S&P 500 index. So much for diversification!

So, is the worst over now for bonds? Maybe not. The future for nominal bonds looks uncertain. We are supposed to believe that with relatively modest rate hikes, to 3.4% by the end of this year and 3.8% by the end of 2023, as predicted by the median FOMC member at the June 14/15, 2022 meeting, inflation will miraculously come under control. As I wrote in my last post, that doesn’t quite pass the smell test because it violates the Taylor Principle. The Wall Street Journal quipped “The Cost of Wishful Thinking on Inflation Is Going Up Too“. I’m not saying that it’s impossible for inflation to easily subside, but at least we should be prepared for some significant upside risk on inflation and interest rates. Watch out for the July 13 CPI release, everybody!

So, trying to avoid nominal bonds, how do we accomplish derisking and diversification? Here are ten suggestions…

Oh, before we get started, I got one favor to ask. Please check out my recent appearance on the awesome **Two Sides of FI podcast:**

Eric, Jason, and I discussed my safe withdrawal rate research and my economic and financial outlook. And don’t call me the grinch of the FIRE community because I had some uplifting words for Eric who plans to retire in 2024.

Back to the issue of rising interest rates. Let me first just point out one little fun fact…

While it’s certainly true that the 10-year U.S. Treasury total return index is now almost 20% below its all-time high, keep in mind that part of the bond drawdown coincided with the equity bull market in 2020 and 2021. In other words, out of the 17.6% drawdown, “only” 10.5% occurred this year. The other portion of the drawdown came between the August 2020 bond market peak and the January 2022 stock market peak, when we still had a nice negative correlation between stocks and bonds. So, diversification from bonds was not completely ineffective. True, bonds didn’t gain when stocks lost. But at least, intermediate (10-year) Treasury bonds **lost less** than the stock market. Thus, a diversified portfolio would have still slightly cushioned the fall of your portfolio. Not as well as in 2008. More like in the 1970s.

In any case, if you’re still concerned about nominal bonds coming under further pressure, here are a few ideas to deal with that risk…

With cash, I don’t mean dollars stuffed into your mattress. Think money market accounts or 3-month T-bills. The advantage is that you can participate in rising interest rates without losing your shirt from that ugly duration effect. Of course, the unpleasant side effect is that nominal yields are still very low because central banks have only recently started raising rates from bargain-basement starting points. It may certainly feel good not to *lose *any money but with an 8+% inflation rate, your money market account still melts at an alarming rate when looking at purchasing power. But it’s a start!

Keep some powder dry and maybe even move that cash back to longer-duration bonds once we get higher Treasury yields. Then ride down the duration effect again, like in the 1980s! And maybe you can boost your money market rate a bit by rotating your money from one intro teaser rate to the next.

One caveat, though: don’t get your hopes too high that this will miraculously generate significantly better outcomes. For example, if we run my Safe Withdrawal Rate Toolkit (see Part 28 of my Series), and calculate the failsafe withdrawal rates by decade, the improvement for the 1960s cohort is pretty meager, see the table below. You get a slight boost from 3.58% to 3.66%, about a 2% boost in the fail-safe retirement budget. That’s not a big improvement for shifting 25% of the portfolio from intermediate bonds to T-Bills!

And also notice that during the 1920s and 1930s you would have done far better with the diversification benefits of bonds. But of course, the exercise here is to focus on the inflationary supply-side recessions in the 70s and 80s, not the deflationary events in the 1930s.

Treasury Inflation-Protected Securities (TIPS) are government bonds that have a fixed real rate of return, i.e., a return over and above an objective and observable inflation index, namely the U.S. (headline) CPI. If inflation is higher than expected then your return shifts up one-for-one. Sweet! That’s the definition of inflation protection!

In practice, you’ll likely not buy the actual TIPS but rather an ETF, like the iShares TIP. Unfortunately, TIPS ETFs have slightly higher expense ratios than nominal bond ETFs, for example, 0.19% per year for the iShares TIPS ETF vs. 0.05% for the overall Treasury ETF (ticker GOVT). Another problem with TIPS: the yields are still painfully low. On July 1, 2022, the yields for 5, 10, 20, and 30-year TIPS were 0.24%, 0.52%, 1.12%, 0.89%, respectively. That’s certainly better than the 0% on I-Bonds, but still very low by historical standards. Talking about I Bonds, here’s the third recommendation…

I Bonds have become something of a superstar in the personal finance community. Part of that is due to the sometimes deceptive advertising like “you can earn 9.62% in six months” as I’ve read the other on another personal finance blog the other day. That’s inaccurate. You currently earn 4.81% over the six-month window, equal to a 9.62% **annualized **simple (non-compounding) interest. But just to be sure, even 4.81% over six months is a very solid return when everything else is dropping like a rock. With the built-in inflation protection, your I Bonds will certainly do the trick, just like TIPS. While I Bonds share a lot of features with TIPS, there are several differences.

First, there are limits on how much you can buy every year. Usually, the maximum is $10,000 per taxpayer per year (i.e., $20k per married couple), so the average retired couple with a seven-figure net worth will not be able to move any significant chunk of their portfolio very quickly. That said, there are some “hacks” for raising this limit. For example, if you own a business and/or trust, you can get another $10,000 per entity. There’s also the option of “over-withholding” your federal taxes by $5,000 every year and then using the $5,000 federal refund to purchase more I Bonds. See The Finance Buff’s ultimate guide to I Bonds for more information. So, if you are planning a slow shift into low-risk assets during the last five years of accumulation, you can use I Bonds as one of those safe assets and accumulate a six-figure sum over the years.

Second, the value of your I Bond investment cannot go down. While TIPS can lose money when the real interest rate goes up – a duration effect just like in the case of nominal bonds – your I-Bonds are protected from changes in the principal. However, if real yields ever go down again then I Bonds will not go up in value either. So, it’s a two-sided sword!

Third, if you sell before the 5-year mark, you lose 3 months worth of interest. But again, in nominal terms, the rate is still very solid, so even if you park your money for a year in I Bonds and lose a quarter of the income you’ll likely be ahead of a money market account with a measly 1.5% interest.

Finally, the current real interest rate stinks! I Bonds currently guarantee a 0% real return, significantly lower than TIPS. With 0% real return you can pull off a 2.5% safe withdrawal rate over a 40-year horizon. With total asset depletion. I Bonds, just like TIPS, serve only as a hedge in case your equity portfolio has a Sequence Risk scenario during the first 5-10 years of your retirement. Currently, they are not a long-term solution in retirement planning!

*Side note: Which one of the two, TIPS vs. I Bonds would I recommend? In light of the lower real yields and all the bureaucracy in I Bonds (annual purchase limit, registration of a Treasury Direct account, etc.), I’d probably opt for the TIPS. On the other hand, the tax efficiency of I Bonds would be a plus. Apparently, you can defer the interest for as long as you hold the bond.* [thanks to commenter Spencer below for pointing this out!]

Historically, gold has been a pretty decent inflation hedge. In fact, it has been a pretty decent hedge against **any **kind of macroeconomic trouble, even demand shocks with disinflation/deflation. If we were to shift the 25% intermediate bonds portion to gold, the fail-safe withdrawal rates would have improved in the 1960s and 1970s. What’s more, you would have seen a slight improvement in the deflationary periods, i.e., the 1920s and 1930s retirement cohorts. Not a bad hedge!

And the usual disclaimer applies here: ownership of gold was severely restricted in the U.S. for several decades, my simulations are more of an “academic” exercise, looking at how a hypothetical investor/retiree with **today’s **asset allocation options (including gold ETFs, gold futures, etc.) would have fared with **historical **asset return patterns.

Yeah, you read that right. Even though the stock market doesn’t like inflation shocks in the short-term, in the long-term, stocks tend to be a decent hedge against inflation. Eventually, corporate profits will catch up with inflation, and drag prices up as well. In fact, among four major asset classes stocks/bonds/cash/gold, U.S. equity returns have put all others to shame over the last 150 years, when calculating the long-term inflation-adjusted returns.

This is probably not a workable solution for *current retirees *because of Sequence Risk. A 100% equity portfolio in retirement would have been far too risky in historical simulations. But if you’re still accumulating assets and your retirement date is still years away, you might just take a chance with the stock market.

In other words, my recommendation of 100% equities during most of the **accumulation **phase (potentially even up until retirement) is still valid, see my SWR Series, Part 43.

How about international stocks? Well, as I outlined in a post a few years ago, if you’re afraid of a massive bear market in the U.S., then there is relatively little room to hide in international stocks because the U.S. is the largest economy and the “consumer of last resort” for a lot of the foreign export economies. Sorry, everybody, we tend to take everyone down with us if there’s trouble! But one could argue that the Federal Reserve tightening path is ahead of most of the other major central banks. The ECB is still below zero. Japan at zero. The Bank of England started raising rates but at a much slower pace. It’s certainly possible that other economies will fare better.

But not so fast, because when rates are increasing faster in the U.S., one would expect the USD to strengthen against most of the other major currencies. Then money invested in foreign equity markets will likely lose value just from the FX effect. That happened in the 1980s under Volcker and again in the late 1990s tightening cycle. In contrast, the meek policy tightening in 2015-2018 saw only a mini-rally, roughly the same size as the current USD rise. But if the 50-75bps rate hikes keep coming at every FOMC meeting, I’d suspect the dollar could move more like the 1980s or 90s than the late 2010s.

So, if you hold investments abroad, you might be better served with FX-hedged funds. But needless to say, there’s no free lunch: FX-hedged funds also have higher expense ratios and they roll the hedging costs into the fund returns as well. But if you like international stocks, at least take the FX headache out of the equation.

The obvious way to avoid your fixed-income portfolio getting hammered from a **duration **effect is to invest in **floating-rate** bonds.

But here’s the catch: If you like floating-rate bonds with low-to-no credit risk and without any duration risk, well, there’s no free lunch. You likely get yields not much different from a money market account. For example, the iShares ETF (Ticker FLOT) most recently distributed $0.0422 per share in June. That’s an annualized yield of about 1.0%, given the $50 share price. I get more than that with my Fidelity money market fund, ticker SPRXX, with a yield of 1.28% as of 6/30/2022.

If you are willing to sacrifice some safety for higher returns, there’s the Invesco Senior Loan Floating Rate ETF (Ticker BKLN). It offers a yield of about 4% (based on a $0.0661 current monthly dividend, $20.27 share price), but comes with some additional credit risk. In fact, year-on-year the fund is down about 2%. In other words, the price dropped and wiped out one year of income and then some. An FDIC-insured money market account would have performed better. But granted, that past loss is water under the bridge, so maybe the floating rate ETFs will eventually catch up and earn a superior return over a simple money market account.

There are many more ETFs in this space. I won’t research all of them but see here for a list of funds sorted by AUM.

Maybe we could increase the risk level even more. That brings me to the next point…

Taking a little bit more risk, we can push up that yield going from bonds to **preferred shares.** A quick recap, preferred shares are a hybrid between stocks and bonds. They pay a set dividend, which can be a fixed percentage or a floating rate, or more complicated combinations. I haven’t found many offerings of preferred share ETFs focusing on floating/variable rates. Global X Variable Rate Preferred ETF (ticker PFFV) is one.

I like to buy the individual shares because it saves me the ETF expense ratio and I can pick and choose the individual preferreds I like most. Here’s my watchlist of Floating-Rate preferreds, see the table below. A few things to point out:

- Notice that most of them are still in the fixed-rate stage, but many of them will transition to LIBOR+x% within the next few years.
- Most of the shares pay dividends that are taxed as (qualified) dividends at the lower (potentially zero) federal income tax rate. But all of the REIT preferred shares (ACR, CIM, DX, EFC, MFA, MITT, NLY, NRZ, TWO) and one of the Citibank preferreds will pay dividends taxed as interest/ordinary income.
- Notice that the interest rate is calculated relative to the $25 notional share value. But the yield is calculated relative to the actual share price. For most of the preferreds, the yield is a bit higher than the quoted rate because the shares are trading below par.

And by the way, I’m keenly aware of the irony here, because, in my Safe Withdrawal Rate Series, I’ve warned about the dangers of chasing higher yields, see Part 29, Part 30, and Part 31. Preferred shares have significant credit risk. In the Great Recession of 2008/9, the preferred market had a drawdown roughly as bad as the stock market. So, if you use preferreds today you will implicitly assume that the potential 2022 market slowdown will be different from the Global Financial Crisis. That’s not a crazy assumption because I don’t see a repeat of the subprime mortgage meltdown this time around. The large global financial sector players (Bank of America, Citibank, Goldman Sachs, Morgan Stanley, State Street, and Wells Fargo) will likely do OK. Smaller and regional players (Keystone, M&T, PNC, etc.) probably too. But I would at most “sprinkle in” the Mortgage REITs. Even though the rates adjust, the profitability of the underlying companies might not look too hot if rates keep going up at 75bps every meeting. Again, those yields certainly look juicy, but be careful with the Mortgage REITs!

Update 7/7/2022: Also check out my buddy Spintwig’s Fixed-to-Float Dashboard: https://spintwig.com/mreit-preferred-share-dashboard/. He’s done a lot of research on the REIT Preferred Shares.

Historically, real estate has been an excellent inflation hedge. No surprise here, because a big chunk of the CPI consumption basket is rent: both actual rentals and owner-equivalent rent. Specifically, the “Shelter” category in the CPI is 32% of the overall CPI and 41% of the Core CPI, according to the BLS. And rental inflation is certainly strong, see the recent Wall Street Journal article on renter bidding wars. So, even if the home price appreciation might have plateaued in many places, at least the rental income cash flow will keep gushing at increasing rates.

Talking about real estate, I always have to address the issue of physical real estate vs. REITs. I prefer the **direct **real estate investment route. Since I don’t want to manage rental properties myself, I outsource the “dirty” work and invest in private equity funds instead, currently at Reliant Group and Imprint Property Group (formerly known as Drever Capital Management). Broad REIT ETFs (iShares USRT and Vanguard VNQ) have experienced roughly the same drawdown so far this year as the broad market. It appears that the past appeal of REIT ETFs is now reversing as yields are finally picking up, as investors who have previously sought higher dividend yields are now dumping their REITs again. I’d stay away from REITs right now, even though some financial “experts” say that REITs are just as good as brick-and-mortar real estate investments.

I saved this one for last because it’s likely only suitable for experienced finance pros and the geeks. The idea here is that if you predict that rates go up faster than everyone else believes, then you arbitrage this through borrowing in a fixed-rate loan and investing in a floating-rate asset. If you were a “Big Kahuna” in the finance world, say a hedge fund or other large institutional investor you could do that very easily with an interest rate swap. Pick how many billions of dollars of exposure you want and contract that swap with a large investment bank.

For the rest of us with 6 or 7-figure portfolios, it’s a bit harder to accomplish that. But not impossible. We could certainly borrow at a fixed rate relatively close to the Treasury interest rate, using the technique I described in a post last year (“Low-Cost Leverage: The “Box Spread” Trade“). Currently, we can do so up to December 2026 (~4.5 years). And then invest the proceeds in a floating-rate preferred share.

The advantage of the box spread loan is that it’s **fully tax-deductible**, i.e., much preferred to your mortgage or HELOC where you’d need to generate a lot of interest expenditures before you even get over the hurdle of the standard deduction, i.e., before itemization on your tax return makes any sense. And the cost is deductible as 60% long-term and 40% short-term losses. So, if you can find some preferred shares with tax-advantaged dividend income, like the PNC PRP at about par that’s paying LIBOR+4.068%, that would be a nice play. Even in the worst-case scenario where the LIBOR goes back to just above zero, you’ll still make enough income to pay for the loan interest. And if rates were to go up that would be even better!

Most regular readers should be familiar with my work on put options writing. The options strategy is up for the year so far. Not a bad deal considering how bad markets performed during the first six months. But admittedly, my performance was not as good as in 2019, 2020, and 2021. But with all the headwinds that’s still OK. The reason I include this only as an honorable mention is that the strategy is not really an *alternative *to bonds. That’s because the options trading is done on margin. Writing put options is not a *substitute *for a bond portfolio. It’s an add-on to an existing portfolio you already have, whether you keep your stocks + nominal bonds portfolio or replace bonds with a TIPS ETF or a floating-rate preferred share.

Here are a few asset classes that may not work very well in the high-inflation environment followed by a Paul Volcker 2.0 scenario:

**Crypto:**Talking about correlations that suddenly switch. Crypto went through the same trouble. Back in the old days, it was heralded as a high-return asset with zero correlation to equities. Now crypto has much higher correlations and especially betas with the stock market, see my post “Crypto is probably a bad investment!” from a while ago. Due to the increased correlations, crypto will no longer diversify your portfolio, but likely add more risk to it. Of course, this works both ways: if inflation is all just a big nothing-burger, the economy avoids a recession, and the stock market rallies again, then crypto assets will likely pick up some of the tailwinds as well. But in the worst-case scenario, I’d expect Bitcoin & Co. to get hammered even worse than stocks and (nominal) bonds. In the two months since the publication of my blog post, Bitcoin is down over 50%. #ToldYouSo!**International stocks without an FX hedge:**If the Federal Reserve is forced to raise rates much faster and much higher than currently anticipated, we will likely see a strengthening in the USD. So, as I mentioned above, if you like non-US stocks it might be wise to hedge the FX exposure.**Preferred shares with fixed rates:**what’s worse than a 10-year nominal bond getting hammered by a duration effect? How about**infinite**-horizon fixed-rate preferred shares? They will have an even worse duration effect. That’s another reason why I stay away from the major ETFs (for example the iShares PFF) for preferred exposure because they have heavy exposure to those fixed-rate preferred shares. With the predictable result that PFF had a drawdown comparable to the equity market this year! In fact, too many of the floating-rate preferred shares in the PFFV fund are still years away from going floating, some of them in 2029 or beyond. Those shares might not be enough of a hedge against short-term rate hikes.

The 40-year-long bond bull market has finally come to an end. What a great run, riding down the bond yields from their 1982 peak all the way to essentially zero in the year 2020. Now we might have an updraft in yields again and safe government bonds might no longer offer as much of a diversification benefit as in the 2000s and 2010s.

If you’re still years away from retirement you might not even need any derisking. Again, refer to my classic post on pre-retirement glidepaths (SWR Series 43) from last year, justifying 100% equities through most (maybe even all) of the accumulation phase. But if you’re close to retirement or in retirement you will likely want to tread a little bit more cautiously than with a 100% equity portfolio.

There isn’t a one-size-fits-all solution. I’m still heavily invested in U.S. equities (#5) and for diversification, I use real estate (#9) and floating-rate preferred shares (#8), even with a little bit of leverage (#10) and some options trading on margin (#11). But I hope I offered a few new ideas for everybody else.

*Title picture credit: pixabay.com*

With the recent confirmation of a Bear Market finally taking hold, I’ve gotten some requests to comment on the situation: Are we going to have a recession? What’s my inflation outlook? What to expect from the Federal Reserve? What does this all mean for us in the FIRE community?

Let’s take a look…

I made this point in a post two years ago pointing out the challenges of pinning down the stock market (and also economic) turning points: If we define a bear market as a drop of 20+% then the bear market is **confirmed **once we hit the 20% drawdown. But the bear market **started **on the day after the previous all-time high. So, we’ve been in a down market since January 4, when the S&P 500 dropped from its all-time high. By only 3 points to 4,793.54. We just didn’t know it back then. Sometimes ignorance is bliss! Why is this important? It’s good news, of sorts, because if go by the average length of bear markets of maybe 1.5-2 years, we’ve already lived through about 5.5 months of it. Yay!

Of course, I always like to issue the warning that the length of the bear market is meaningless. What matters is how long it takes for the market to recover and reach the next all-time high again, which could take many more years. And when adjusting the portfolio for inflation the recovery can sometimes take a decade or more, as I outlined in my old post “Who’s Afraid of a Bear Market?” in 2019.

Not every bear market is accompanied by a recession. All of the prominent ones were, but we’ve had a few without a recession, for example in 1987. And a few “close calls” like the fourth quarter of 2018.

In any case, what’s the economic outlook? Am I worried about a recession? I’m no longer a full-time economist. Even the short consulting gig as a “Chief Economist” for a startup only lasted for only a year in 2021. So, not willing to run a big forecasting model, which is at least a part-time maybe even a full-time job, I like to keep things simple. As I introduced in a 2018 post, here are the three indicators that I like to follow as a hobby-economists to monitor the health of the economy and the prospect of an economic slowdown:

**1:** **The slope of the yield curve** is one of the most reliable recession indicators. At some point before the start of the recession, all those smart folks working as fixed-income traders apparently sense that the Federal Reserve will first yank up rates and then lower rates again 1-2 years down the road, in response to the slowdown. This will push short-term rates higher and long-term rates lower. And apparently, those fixed-income folks were so smart that they even predicted the 2020 pandemic recession with a very brief yield curve inversion in August 2019. Some of them must be virologists, who knew?! Joking aside, financial markets probably didn’t have any inside knowledge and even without the pandemic, there might have been an economic slowdown around the corner.

In any case, that yield curve signal again flashed (slightly) red in early April of 2022. It’s a slightly worrisome signal, but the brief and very shallow YC inversion isn’t that concerning. For example, in 1998 we had a similarly meek inversion and the recession took another 3 years to take hold.

**2:** **Weekly Unemployment Claims **have been a pretty neat signal in the past. Every past recession was preceded by a sharp rise in the weekly unemployment insurance claims. Even though the NBER business cycle timing committee uses the monthly payroll employment numbers in determining the business cycle turning points, I like this series better because it’s at a higher frequency and doesn’t have to deal with those pesky benchmark revisions like the payroll series. In any case, according to this series, we’re still looking great. Unemployment claims are close to their post-pandemic lows, around 200k. Neither level nor direction indicates an imminent recession risk.

**3: The Purchasing Managers Index (PMI)** is another important economic health indicator. During or even before recessions, we’d normally observe a marked fall in the PMI index, usually below 45. Of course, anything below 50 is already looking shaky. In fact, the level of 50 is the +/-0 line between contraction and expansion, but there have been a few “false alarms” when the PMI fell to a level between 45 and 50. Below 45 seems to be a clear sign of the economy doing poorly. Right now, we’re still above 55. In fact, in May the PMI even edged up slightly to 56.1 from 55.4 in April. While the PMI readings have certainly come down from their 60+ levels in the Spring of 2021, we’re still looking pretty solid. No recession warning signals are flashing red here!

So, with my recession indicators, we’re 1 for 3. Hey, maybe only 0.5 for 3, if we factor in how brief and shallow the YC inversion was. So, the economy still seems to chug along. Everybody should be happy about that, right? Right? Uhm, maybe not. You see, in a perfect world, the Federal Reserve will slowly tighten the policy rate to about 4% by next year, inflation pressures will slowly abate, and we avoid a recession as well. The perfect soft landing. In a blog post five months ago, that was my personal prediction. While I still **hope **for this scenario, I’m almost sure that the path of the economy will be bumpier. The big gorilla in the room: Inflation! Notably, there are **two unpleasant observations:**

**1: Inflation doesn’t seem to go down on its own.** Thankfully, we’ve now retired the “transitory” moniker. The year-on-year CPI just posted a 40-year high. How is that possible? True, we’re now phasing out the strong inflation readings from the Spring of 2021. But we’re now replacing them with even worse monthly CPI numbers. And thus, the nasty CPI surprise on June 10 set off the whole equity selloff.

And the June 2022 CPI reading (released on July 13) will probably be another bummer, looking at the energy price surge in June month-to-date. What’s worse, it’s not just food and energy prices. A slow-moving train wreck is coming our way, in the form of shelter (i.e., rental) inflation, both for actual rental units but also for owner-equivalent rent (essentially derived by extrapolating the market rent to the owner-occupied market). Rental inflation factors in rises in real estate prices as well as interest rates but with a delay. In the chart below, notice how the shelter CPI trough lagged the overall CPI trough by about a year. In other words, rental inflation stayed relatively benign during the early part of the inflation shock. But the rental inflation train is now gathering steam. Housing is the largest component of the Core-CPI! A quick decline in year-on-year CPI numbers is certainly off the table. And we might even see further acceleration. Buckle up, everyone!

**2: Contrary to the public’s perception, U.S. monetary policy isn’t tight at all.** Quite the opposite, the Federal Reserve effectively continues to pour gasoline on the inflation fire. How is that possible? Isn’t the Fed raising rates already? 75bps at the meeting today, on June 15! That sounds like monetary tightening, right?

Well not really. What matters for **real **economic outcomes is the **real**, inflation-adjusted policy rate. Right now, that real FFR is still close to its all-time low. Consequently, in response to a worsening inflation shock, our current monetary policy is actually more accommodative than at the bottom of either the Global Financial Crisis or the Pandemic Crash when the central bank accommodated with a real FFR in the -3% to -1% range. In other words, the real FFR is now lower than when everyone ran around with their hair on fire, worried about **deflation**. The Fed raised the real FFR to around 3% above trailing inflation during the 2000 and pre-GFC tightening cycles. Even in 2018, we at least reached a (slightly) positive real short-term rate.

Let’s face it, we won’t see any true monetary tightening until short-term rates exceed the inflation rate! By that measure, **the Fed is about 6-7 percentage points behind the curve. **It would take many more rate hikes to correct that. Ouch!

How did this happen? Very simple, my former colleagues at the Federal Reserve apparently forgot about a very simple monetary economics doctrine: the **Taylor Principle**, named after famed Stanford economics professor John Taylor. I would summarize the principle as follows:

Taylor Principle:The central bank should move the nominal policy interest rate bymore than one-for-onein relation to inflation shocks. This produces a tightening effect in the form of arealinterest rate hike, slowing down demand and reducing inflation pressures.

But I don’t want to ding the Fed too badly. It was easy to get complacent. During the entire post-GFC era, even the post-2001 era, economists were puzzled that despite massive and prolonged monetary and fiscal stimulus, inflation didn’t rise much. What a conundrum! It was easy to forget basic economic lessons.

The image that comes to my mind is that of someone trying to start a BBQ, pouring copious amounts of lighter fluid on the grill. The thing still doesn’t start. Let’s empty another bottle! We need more stimulus! And then it does start and almost sets the whole neighborhood on fire. That person with the singed hair and eyebrows: that’s how the Federal Reserve is feeling now.

What would be the easy way out of this mess? A mild recession right around the corner could be a blessing in disguise! It would likely break the self-fulfilling prophecy inflation spiral. It would take pressure off of energy prices. New and used car prices could return to normal levels. You might be able able to get a rental car again at reasonable prices! That’s because during recessions, even mild recessions, consumers like to tighten their belts. Spending less on durable goods and discretionary items always does the trick.

If we don’t have that marked slowdown soon and prices don’t come down on their own? Expect rate hikes at 50-75bps every meeting. At least we don’t get a 200bps hike in one meeting, as proposed by Jeffery Gundlach! Either way, the Fed will raise rates until inflation subsides. In all likelihood, that will eventually trigger a recession if the Fed has to go into a full Paul-Volcker mode.

Again, I don’t want to sound like a doomsday preacher. I certainly prefer the scenario where we can thread the needle and everything still works out all right. But absent that optimistic scenario, I prefer the near-term mild recession. Let’s just get it over with! Let Paul Volcker rest!

The usual disclaimers apply: it depends on where you are on your FIRE journey. If you’re still years away from (early) retirement, you probably should not stress out over this. Automate your savings and investments. There is no point in trying to time the market. Remember the old advice “time in the market is more important than timing the market.” My retirement plan contributions during 2001-2003 and then again in 2007-2009 were some of the best investments I ever made, thanks to dollar-cost-averaging. This bear market will turn around again. In fact, following a painful inflation episode and the Fed sinking the economy in 1982, we had one of the longest and most robust equity bull markets. Stay the course, everyone!

If you are close to retirement or even in retirement, you have more reasons to worry. Going through a bear market is more damaging to your finances when you are taking withdrawals already. It’s called Sequence Risk and I have written about it extensively. Readers of my blog and my Safe Withdrawal Rate Series will likely start with a conservative enough withdrawal strategy that would have withstood even the Great Depression. A 20% drop in the stock market is nothing compared to that. Also, check out Part 37 of the SWR Series, with my recommendations during the 2020 bear market. For example…

After we’ve already fallen by 20+% we can be a lot more generous with our safe withdrawal rates. Historically, you can use withdrawal rates well in excess of 4% if the stock market is down as much as today!

SWR Series, Part 37.

Yup, you’ve heard it here first: The 4% Rule probably works again in today’s environment, after the market dropped by 20%+!

Another question I frequently get: Now that the stock market is down, should retirees shift to 100% equities again? If the bear market stays relatively shallow and rebounds quickly you might look really smart. But again, in Part 37 of the series, I point out that during the really catastrophic equity bear markets, going all-in too soon would have backfired spectacularly.

**Update 6/15/2022, 6PM**:

Since someone asked: with the recent drop in the S&P index, how does the valuation look like now:

- With the 6/15 close of 3789.99, my CAPE now stands at 28.6. We can’t use the Shiller numbers because the index and earnings data are outdated. That CAPE is still 80% higher than the historical median.
- I also compute an adjusted CAPE that accounts for different corporate taxes and earnings payout ratios. The adjustment lowers the CAPE to 22.9. Still elevated but not that bad. 45% higher than the median.
- PE ratio using 12-month trailing earnings: 18.9. Only 27% higher than the historical median.
- PE ratio using 12-month forward earnings estimates: 17.2. 20% higher than the historical median.

*Title picture source: pixabay.com*

In this year’s April Fool’s post, I marketed a made-up crypto coin that would completely hedge against Sequence Risk, the dreaded destroyer of retirement dreams. Once and for all! Most readers would have figured out this was a hoax because that complete hedge against Sequence Risk is still elusive after so many posts in my series. Sure, there are a few minor adjustments we can make, like an equity glidepath, either directly, see Part 19 and Part 20, or disguised as a “bucket strategy” (Part 48). We could very cautiously(!) use leverage – see Part 49 (static version) and Part 52 (dynamic/timing leverage), and maybe find a few additional small dials here and there to take the edge off the scary Sequence Risk. But a complete hedge is not so easy.

Well, maybe there is an easy solution. It’s the one I vaguely hinted at when I first wrote about the ins and outs of Sequence Risk back in 2017. You see, there is one type of investor who’s insulated from Sequence Risk: a buy-and-hold investor. If you invest $1 today and make neither contributions nor withdrawal withdrawals, then the final net worth after, say, 30 years is entirely determined by the compounded average growth rate. Not the sequence, because when multiplying the (1+r1) through (1+r30), the order of multiplication is irrelevant. If a retiree could be matched with a saver who contributes the exact same amount as the retiree’s cash flow needs, then the two combined, as a team, are a buy and hold investor – shielded from Sequence Risk. It’s because savers and retirees will always be on “opposite sides” of sequence risk. For example, low returns early on and high returns later will hurt the retiree and benefit the saver. And vice versa. If a retiree and a retirement saver could team up and find a way to compensate each other for their potential good or bad luck we could eliminate Sequence Risk.

I will go through a few scenarios and simulations to showcase the power of this team effort. But there are also a few headaches arising when trying to implement such a scheme. Let’s take a closer look…

We’d need to pair up a retiree and a saver or groups of retirees and savers whose cash flows exactly cancel out each other. Then at the end of the contract period, both retiree and saver will receive a respective portfolio value they would have achieved had the return pattern been one flat monthly or annual return matching the CAGR during the contract period, i.e., in the absence of Sequence Risk.

Imagine, for simplicity, that we have a retiree with a $1m initial portfolio with $40,000 in annual cash flow needs and a retirement saver who starts with a $0 portfolio and saves $40,000 annually. Assume that they agree to offset each other’s cash flows over a set contract period to generate a buy-and-hold investor if aggregating the two cash flows. For any realized buy-and-hold investor CAGR over this period we can now calculate the final values of the retiree and saver portfolios using the Excel future value (FV) function:

```
=FV( CAGR ,Nyears , 40000,-1000000,1) (retiree)
=FV( CAGR ,Nyears ,-40000, 0,1) (saver)
```

And again, notice how the final values depend solely on the CAGR. Not on the Sequence of Returns! In any case, before we even get into any simulations, let’s run a simple example to warm up. Imagine both retiree and saver like to eliminate Sequence Risk over a 10-year horizon. They may each have a longer horizon, but they decide to sign this pact over a 10-year horizon, so bear with me.

Let me first illustrate the workings of Sequence Risk again. Let’s assume that over the 10-year horizon a portfolio of risky assets returns 5% (inflation-adjusted) on average, measured by the CAGR. Let’s assume that returns can be High (+29.71%), Moderate (5%), or Low (-15%). Why that crooked number of 29.71%? Simple, that ensures that one high and one low return combined get you back exactly to 5% CAGR. Check the math if you like: 1.2971*0.85=1.1025=1.05^2! Now let’s look at 7 different sequence risk scenarios. We can start with the “MMM” scenario where we have flat 5% returns every year, plus 6 additional scenarios: each with 6 years of moderate returns, 2 years of high, and 2 years of low returns in varying orders. Notice again that all 7 scenarios have the same CAGR:

We can briefly confirm that a buy-and-hold investor achieves the same final net worth regardless of the order of returns. Here’s a chart:

And below is a table with the same information. Notice again that the final value has to match up exactly, even though the path over time can be very different:

While the buy-and-hold investor is shielded from Sequence Risk, the retiree will certainly not be indifferent to the sequence of returns. Here’s a time series chart of the retiree, starting with a $1,000,000 portfolio and withdrawing $40,000 each year (at the beginning of the year). Notice that the balances are plotted before the withdrawals. So X(0) = $1,000,000 and X(t)=[X(t-1)-$40,000]*[1+R(t)], t=1,…,10.

Now we get some action! The final balances range from $887k to $1.244m. The most advantageous scenario is when the high returns hit first and the low returns come last, and vice versa – no surprise here!

The same info is in the table below. Notice how this retiree’s IRR can be significantly different from the realized CAGR, all due to Sequence Risk. If a retiree had committed to this RSIP contract, he or she would be guaranteed to walk away with $1,100,623 after 10 years, regardless of the sequence of returns. So, for example, under the HML scenario, the retiree would give $143,578 (=$1,244,201-$1,100,623) to the saver. But in the worst-case LMH scenario, the retiree would receive $213,333 ($1,100,623-$887,291) from the saver.

Now the same exercise for the saver:

And all that again in a table format below. Notice how the range of IRRs is even wider for the saver (makes sense due to the $0 initial balance). It’s quite intriguing how merely reshuffling the *order *of returns will transform a 5% CAGR into anything between a -0.71% to +10.98% IRR. The best-case scenario (LMH) gives you almost a 2x relative to the worst-case scenario (HML). All due to Sequence Risk!

And just to confirm, the payments are now exactly flipped: In the HML scenario, the saver would receive $143,578 from the retiree, while in the LMH scenario, the saver would pay $213,333 to the retiree. This would exactly guarantee a $528,271 payout for the saver, regardless of the sequence of returns. Pretty cool!

Summary so far: If a saver and retiree could sign a binding contract to balance their portfolios back to the “MMM” scenario, i.e., flat returns equal to the realized CAGR, then we could certainly take a bite out of Sequence Risk. It’s also important to note that it’s not just the retiree who would benefit from this scheme. Savers face significant Sequence Risk. In other words, to all of us who retired recently, let’s not get too cocky. Our investment success is mostly due to luck in the form of both high average returns and a very advantageous Sequence Risk outcome: low in 2008/9, moderate for a few years, and then spectacular in the latter part, especially in 2019/2020/2021. The next cohort of savers may not be so lucky and can certainly benefit from such a scheme!

Let’s run some historical simulation with actual return data 01/1871-04/2022. Let’s assume again that the initial portfolios are $1m for the retiree and $0 for the saver and the annual withdrawals of $40,000 exactly offset the annual contributions of the saver. To be consistent with my other SWR work, I assume that we run this at a *monthly *frequency (=$3,333.33 of monthly withdrawals/contributions). The time horizon is 30 years and the retiree has a 75% stock, 25% bond portfolio (intermediate 10-year U.S. Benchmark Treasury bonds). The account values and withdrawals/contributions are adjusted for inflation, as always.

Let’s first look at the final outcome the retiree could achieve without the scheme, i.e., when subject to Sequence Risk (blue dots) and with the RSIP, i.e., when hedging the Sequence Risk (orange dots) in the chart below. Luckily for the retiree, even at the lowest 30-year CAGR, you would not have run out of money. But without the RSIP there were plenty of occasions where you would have depleted your portfolio. Intriguingly, the retirement bust scenarios occur when the 30-year CAGR of the buy-and-hold 75/25 portfolio was between about 3.8% and 6.5%. This confirms again that Sequence Risk is a much larger headache than merely low average returns. Over a 30-year horizon, you need a mere 1.3% flat real return to exactly deplete your portfolio. That’s a low bar. All the retirement failures are squarely due to Sequence Risk, not the CAGR falling below 1.3%!

And the same for the saver, see below. Clearly, the saver will not run out of money but look again at the dispersion of the blue dots around the orange line: Several million dollars in final value uncertainty. A lot of retirement savers may be willing to give up the upside to hedge the downside risk. Give up the prospect of a $7m retirement portfolio but vastly reduce the possibility of falling short of $2m.

Instead of plotting the final values, we can also calculate the IRR for the different retirement and saver cohorts. Excel has a neat function for translating a present value (PV), a future value (FV), and regular payments into an IRR.

```
=(1+RATE(360,0.04/12,-1,FV,1))^12-1 (retiree)
=(1+RATE(360,0.04/12,0,-FV,1))^12-1 (saver)
```

Notice that I run this at a monthly frequency, so the payments are 0.04/12, but then the IRR has to be annualized.

Let’s plot this for the retiree first, see below. I plot the actual retiree cohort IRRs (blue dots) and also a 45-degree line because that 45-degree line is the IRR you could have gotten with the RSIP, i.e., in the absence of Sequence Risk.

Again: you win some, you lose some. The blue dots are scattered wildly around the CAGR. For example, this chart demonstrates how Sequence Risk can turn a 6% CAGR for the buy-and-hold investor into a -1% IRR for a retiree. By the way, this cohort with the -0.73% IRR is the December 1968 cohort. The average return from December 1968 to December 1998 was an impressive 6.02% (real). But due to Sequence Risk, the retiree got shafted with a negative IRR (while the Dec 1968 saver cohort got a +9.30% IRR!).

And the same for the saver, see the chart below. Again, we get a wide dispersion of IRRs around the 45-degree line. The historical range of IRRs ranged from 1.5% to 9%, while the realized IRRs of the saver ranged from -0.5% to just under 10%.

At first glance, this seems to be an easy way to accomplish a hedge against Sequence Risk. Hey, maybe we could run our own little FIRE quasi-pension fund. But the devil is in the details. Here are a few headaches I can think of:

**Asset allocation:** Savers and retirees may not want to hold the same asset allocation. For example, fresh retirees will likely opt for a slightly more conservative asset allocation, maybe about 75% stocks and 25% diversifying assets like longer-term bonds and/or short-term fixed income instruments, while young savers might want to be more aggressive. That’s not really an insurmountable obstacle because if young savers prefer 100% equities then the retirees may then contribute only their equity portfolio to the pact. And maybe construct a bond ladder to supplement the retirement income.

**Horizon: **retirees and savers might have different time horizons. For traditional retirees (30-40 years horizon) and retirement savers (also a 30-40 years horizon), this might all work really beautifully. But in the FIRE community, we have this slightly lopsided distribution: maybe 10-15 years of accumulation and then 40-60 years of retirement. Of course, one retiree cohort could always be paired with a new set of fresh FIRE savers once the current one archives financial independence. But the problem with this idea is that in order for the RSIP to work we’d need to ensure that the duration of the pact is long enough that a long stretch of bad returns can be offset by a new bull run. 10-15 years might not be enough. There were plenty of poor return windows for the stock market: 1929-1942, 1965-1982, 2000-2009 when a 10-15 year window would have been too short to effectively hedge against sequence Risk. You would have needed the subsequent 10-15 years to truly smooth out that Sequence Risk. 20-30 years seems to be the minimum to capture enough of a large macrocycle to include both poor and blockbuster returns.

Maybe the solution would be to pair traditional retirement savers with a 30-40-year horizon with FIRE enthusiasts and cover their first 30-40 years in retirement. FIRE savers with their short horizons may be less-than-ideal candidates for this scheme.

**Taxation: **The flows between two parties in this pact will likely draw the attention of the IRS. How do we tax the transfers from one group to the other? Capital gains? Ordinary income? How do we deal with the cost basis in taxable accounts? My suspicion is that this plan would work best if we implemented it in a retirement account where we don’t have to deal with a lot of the taxation issues of reshuffling assets.

**Safety:** Before I hand over any sum of money I’d need to see some assurances that people won’t abscond with my hard-ERNed cash. We could implement this RSIP through a reputable financial institution, think Fidelity or Vanguard. Or an insurance company. Or maybe this is a blockchain application where we could cut out the greedy financial companies and do this peer-to-peer start-to-finish. Some silicon valley whiz-kids might want to take a shot at this!

**Commitment:** Both parties – saver and retiree – will **initially **enter this pact voluntarily and willingly, because on an ex-ante basis it is advantageous to hedge against risk. But people might regret this pact ex-post after the asset returns have come in. No, let me correct this, exactly one side of the deal will **most certainly **regret participating in the deal. Because that’s the whole idea of this peer-to-peer insurance contract: one side’s gain is the other side’s loss. We only enter this insurance contract because we believe that there could be some large net payments and ex-ante we prefer to minimize the risk. If I find out, ex-post, that Sequence Risk helped my portfolio, I’d rather run with my money instead of sharing some of the Sequence Risk gains.

And this commitment problem is worse for the saver who needs to contribute the regular flows. Maybe institutional investors like pension funds could take the side of the saver. That would be a challenge again, though, because it would have to be a “young” pension fund with mostly savers and very few retirees and thus net inflows. The current pension fund landscape is the exact opposite: most companies have phased out their defined benefit plans and replaced them with defined contribution plans. The existing pension funds still around are mature funds with mostly aging beneficiaries and net outflows. Not much help there!

Also, the **willingness **for continued participation is not always the biggest problem. There’s also an issue with the **ability to participate:** This is less of an issue for the retiree who simply sits back and collects $40,000 checks every year. But a huge concern for the saver. What if savers lose their job, die, or become disabled?

**Retirement ruin: **Even though both parties hedge against sequence risk, there is no insurance against the average realized asset return. If the average equity return is low enough then the retiree can still run out of money. Historically, there would have been a few cases where a $40,000 annual withdrawal would have wiped out a 100% equity portfolio even with the RSIP.

Summary so far: Maybe this RSIP is mostly a cute theoretical construct but not so easy to implement. I’m open to suggestions for how to make this work in real life. Please use the comments sections if you want to help.

But maybe we could implement transfer payments without a specific counterparty. This brings me to the next point…

Is it possible to generate the sequence-contingent transfer payments just on my own? Without any direct counterparty that may or may not be willing to adhere to the multi-decade investment pact? One way would be to devise a derivative-based strategy to at least roughly mimic the transfer payments between the retiree and the saver. The advantage of this approach is that many of the headaches listed above will go away. For example, if I were to generate transfer payments modeled after this strategy through exchange-traded derivatives I would not have to worry about my counter-party walking away from the deal. *(well, there is a minute risk of both the counterparty and the exchange going belly-up simultaneously, but let’s not even go there…)*

Taxation would also become a lot clearer: Index futures and options enjoy tax-advantaged treatment under IRS Section 1256, as my readers know from my options-trading posts. One obstacle, though would be that, some options strategies may work only in taxable brokerage accounts, not in retirement accounts!

There may be many different ways to structure this, but the most obvious one is this: Imagine a retiree expects a target real return of 4% p.a. over a 30-year horizon and a 4% annual withdrawal rate. And for this simple example, I go back to annual withdrawals, taken at the beginning of the year.

Imagine that in year 1, this retiree suffers a 10% drop in the portfolio. Assuming that during the remaining 29 years we revert back to the 4% target we can project the portfolio’s final value. That’s what I did in the table below. The retiree is expected to end up with $491,117 (in real, inflation-adjusted dollars). If the retiree had access to the RSIP, SoRR insurance we can calculate the 30-year CAGR as 3.50%, i.e., CAGR of one year of -10% and 29 years of 4% return. The projected final portfolio value in the absence of Sequence Risk, i.e., with a fixed 3.5% rate of return, is $669,611. So, if you had access to Sequence Risk hedging you’d stand to get a transfer of $178,494 in year 30. Discounting this payment back to year 1 at an annual rate of 4% would amount to $57,234.

We can also calculate this transfer payment for several different Y1 returns. Let’s calculate the transfer payment for Y1 returns of -15%, -10%, -5%, 0%, 4%, 10%, 15%, 20%, and 25%. Obviously, the transfer has to be zero for the Y1 return of 4%, but it’s good to confirm and check the math. I plot the scatter plot of the Y1 return (x-axis) vs. the transfer payment (y-axis) in the chart below:

That line is almost a perfectly straight line. That’s not too surprising because even though the future value after 30 years is a non-linear function, by taking the difference between the two versions, once with and once without SoRR, we generate a function almost exactly straight. This particular line has a slope of about -$400k and an intercept of just under $17k.

So, how could we replicate this blue line with a derivatives strategy? It’s not that easy! We could certainly sell a futures contract with a notional of $400,000. But we wouldn’t be able to get the $17,000 intercept.

Likewise, we could sell $400,000 of the risky assets to exactly replicate the slope of the blue line. But in taxable accounts that might become a big headache from a taxation perspective given our progressive income tax function. And even in tax-deferred accounts, selling assets is useless unless we find a safe investment with a 4.25% return (17,000/400,000=0.0425=4.25%) to shift the line up to its intercept. I-Bonds currently yield 0% above inflation, TIPS also around 0%, and nominal bonds around 2.1% for one year, which will likely get you to -4.25% rather than +4.25% after inflation. Not a pretty sight! In fact, if we had access to a 4.25% safe return, we wouldn’t have to worry about Sequence Risk and hedging against an uncertain Y1 return, would we? We would just move the entire portfolio to that asset, raise the withdrawal rate to 4.25%, always preserve our portfolio, and live happily ever after.

One could argue that after a big drop in the stock market, we’d likely also expect slightly higher returns return in years 2-30, from a valuation point of view. By discounting at a higher rate we might be able to push that intercept down a bit. But not by much. Not by enough to bring the required return down to the 0% real return we face today.

I guess the perfect solution to Sequence Risk is still elusive. The RSIP is a cute theoretical and mathematical concept but implementing it directly through a retiree plus saver partnership faces a lot of obstacles. On the top of the list is the commitment problem of the saver. Maybe an insurance company or large brokerage company could take the counterpart and offer Sequence Risk insurance to retirees. But I’m concerned that the fees involved would likely wipe out any potential gains. Trying to implement a transfer payment scheme through a derivatives strategy is also an uphill battle. But I’m open to suggestions. Please share in the comments section if you have better ideas on how to make this work!

*Title Picture credit: pixabay.com*

If you remember my April Fools Day post from a few weeks ago, I poked fun at the proliferation of new crypto coins. Most of them are scams. But what about the mainstream crypto coins, like Bitcoin, Ethereum, etc.? Are they a good investment? What’s not to like about a 100%+ annualized return in some of the crypto coins between their inception and their 2021 peak?

Well, those returns are “water under the bridge”. What matters to me today is the outlook for the crypto world going forward. In today’s post, I like to go through some of the reasons why I believe going forward, crypto looks like a sub-par investment. I currently don’t invest in crypto and I don’t think that anything more than a few % of the portfolio seems prudent. Let’s take a look…

To pay respect where respect is due, let’s just get the obvious out of the way: cryptocurrencies had very impressive returns. I downloaded the crypto return series I could quickly retrieve from the web: the S&P Cryptocurrency LargeCap Index and three individual coins: Bitcoin, Ethereum, and Litecoin, with the data coming from the St. Louis Fed “FRED” database. In the chart below is the cumulative (nominal) return since 2017. (Note that the S&P Crypto index only starts on 2/28/2017). The cryptocurrencies had spectacular returns. Ethereum with 360x, Bitcoin at about 41x, Litecoin at 24x, and the Large-Cap crypto index with 20x (though with a slightly later starting date of 2/28/2017). I had to display the y-axis in logs because otherwise, you wouldn’t even notice the S&P 500 stock index and the 10-year benchmark bond index (Source: www.spglobal.com). The S&P 500 merely doubled in value (and that’s not even CPI-adjusted), and the 10-year Treasury Benchmark bond index is essentially flat over the 5+ years.

Even the spectacular and sky-high past returns look a little bit more down-to-earth when factoring in the risk you have been taking with the crypto investment. In the table below I display the annualized return stats – annualized return, annualized volatility (= monthly vol times sqrt(12)), and the Sharpe Ratio – and again compare and contrast them with the S&P 500 and 10-year Treasury benchmark bond returns. I display the results for three different time periods: 1) the entire interval since 2017 and the pre- and post-pandemic period.

Average annualized returns for crypto assets were in the high double-digits and even triple digits while the S&P 500 (TR) returned “only” about 16.5% since 2017. Nominal bonds only 2% until the end of March 2022. But the cost of double and triple-digit returns is the double and triple-digit risk inherent in the crypto market. And due to the extraordinary volatility numbers the Sharpe Ratios, i.e., the risk-adjusted excess returns over a risk-free benchmark, look not too different from the S&P 500 over the 2017-2022 time span. Ethereum and Bitcoin did a little bit better than the S&P 500, especially during the second half of the sample. Litecoin did worse than the S&P 500.

Also evident in the cumulative return chart: all assets have been under pressure since late 2021. I am not saying that a temporary breather like we’ve seen over the last 6 months is a dealbreaker and automatically makes crypto a bad investment. Heck, stocks and bonds are going through the same phases all the time, including right now. What’s a bit more worrisome is that while stocks are holding up OK right now (a drawdown of about 10% as of April 25, 2022), the two major crypto coins are down 40% (and so is the large-cap index) and the smaller Litecoin is down 70%. Ouch!

What’s more concerning than the 40% crypto drawdown is that crypto has also become a lot more correlated with equities, which brings me to the next point:

Occasional drawdowns shouldn’t be too much of a concern if that asset is uncorrelated with the rest of the portfolio. And for the longest time, that was certainly the case with the cryptos. But if I calculate the correlations over the three samples again (full sample, 2017-2019, 2020-2022) we notice that the correlation between the crypto assets and equities has noticeably risen, see the table below:

I can also confirm that the higher correlation is not merely due to the 2020 pandemic volatility. In the chart below, I plot the 12-months rolling correlation with equities. The strong correlation still holds up after rolling out the pandemic bear market. Anything with a market cap approaching $1t will start having some correlations with the business cycle and other risky assets!

Even worse than the correlation, the “betas”, i.e., factor model regression slopes of the crypto returns vs. the equity returns have been substantial. In the table below I display the factor model regression results, i.e., regress crypto (excess) returns on (excess) returns of stocks and bonds. In the second part of the sample, the index and all three coins have substantial and significant beta exposure to the stock market. For example, the 3.25 equity beta and 1.81 bond beta for Ethereum signal that this coin behaves close to a 3.25x leveraged equity plus 1.81x bond portfolio. But I also concede that in addition to the factor exposure, there are significant intercepts (alphas) in all of the coins. Even significant in the case of Ethereum. Though I doubt that Ethereum will keep paying an 11.7% (monthly!) excess return over a 3.25x equity portfolio forever!

But does this all mean that cryptocurrencies are a bad investment? Not necessarily. It depends on the outlook for crypto returns going forward. This brings me to the next section…

If we believe that Bitcoin and Ethereum will again return 127% or 300% annualized, respectively, over the next few years then we’re done. No analysis is needed, then. But I think we can all agree that this kind of run cannot continue forever. With a current crypto market capitalization of $1t, it would only take a few more years before crypto assets are worth more than everything else on earth. Herb Stein’s law comes to mind.

So, what would be an appropriate expected return for the crypto assets? Well, just purely from the beta exposures to the stock and bond market index data, we could set the expected return of the crypto-assets the way you’d do in any other factor model application. For example, if Ethereum has an equity beta of 3.25 and a bond beta of 1.81, then the expected excess return is the beta-weighted sum of stock&bond returns, though adjusted by the cash rate for the portion of the total beta exceeding 1.0. That’s because if you invest in stocks or bonds on margin you have to account for the margin rate and subtract that again.

Then, if we calibrate the inputs as:

- Stock expected returns 8% (3% inflation plus 5% real return),
- 10-year Treasury bond expected returns 3%,
- and the cash/money-market rate as 2.5% over the next 10 years,

… then we get the following expected returns:

- Bitcoin: 14.5%
- Ethereum: 21.3%
- Litecoin: 19.2%
- S&P Large Cap Crypto Index: 16.1%

So, even without including any additional alpha, these are very impressive expected returns. If we assume a current market cap of $1t in the large-cap crypto market and a 16.1% overall index growth, then we should expect almost $4.5t in market cap in 10 years. Pretty impressive. With those expected returns, what kind of crypto portfolio weights can we justify? That brings us to the next section…

With the variance-covariance matrix constructed from the post-2020 return data and the forward-looking return data, we have all the tools necessary to construct efficient frontiers with and without crypto assets. I start with the traditional assets only (stocks&bonds), then add the SP Global Large-Cap Crypto Index, and then all four crypto assets (index + 3 individual coins). The efficient frontiers are in the chart below.

*A technical note for the finance purists: The efficient frontiers should stop at the min-vol portfolio and not continue below in the south-easterly direction. Lowering return and increasing risk is clearly not efficient. At this point, I leave that portion, but normally I would plot that “inefficient” as a dotted line. The charts were made with Python instead of my usual Matlab/Octave, so please bear with me*

I can also look at the portfolio allocation for different expected return targets, see below. Crypto assets don’t enter the portfolio until about 5.3% expected return, and even then we only add them very slowly. Only for 8.75% and higher target returns would you start adding the crypto assets aggressively. That makes perfect sense because you can get only a max return of 8% from the traditional asset mix. But if you’re targeting any kind of expected return similar to a 100% equity portfolio, there’s very little crypto in the portfolio. Maybe a 4-5% share.

Of course, the crypto assets are indeed useful if you’re interested in going beyond the “normal” range. But how much of the “interesting range”, say, 20% and less volatility, is really improved by the crypto assets? Let’s zoom in and look at the chart below. Not much of an improvement. The efficient frontiers with crypto are essentially right on top of the green parabola that uses only stocks and bonds. Crypto doesn’t help you if you demand a portfolio with a volatility less than a 100% equity portfolio.

The problem with any kind of portfolio optimization method, including efficient frontiers, is that the results are very sensitive to the expected returns we use. I don’t want to be accused of low-balling the expected return assumptions. Especially in light of the large alpha estimates in the factor model regression above. So, how about I slap on an additional 10% expected return to all the crypto-assets. Maybe there’s an additional risk factor that I’m not capturing and the 10% extra returns account for that. But a 25-30% annualized return seems unrealistic over the medium-term because I don’t quite see how the crypto market cap can increase by a factor of almost 14 over the next 10 years (1.3^10=13.79). So, under those unrealistic assumptions, crypto assets will indeed make a noticeable difference in the efficient frontiers, even in the sub-20% risk region. But I don’t believe expected returns are that high.

I can also plot the weights of the various assets as a function of the portfolio expected return again. Targeting a 10% annualized expected return, you’ll indeed include about 20 % crypto-assets.

But again, I don’t find the expected return assumptions very realistic.

If you’re troubled by the way I calibrated the expected returns, there are also a few portfolio construction ideas that work entirely off of the variance-covariance matrix (VCV), thereby sidelining the expected return inputs. Min-Vol portfolio and Risk Parity come to mind. Can crypto assets play a role here? Well, let’s take a look:

**Risk Parity** targets portfolio weights to equalize what different asset classes contribute to the overall portfolio variance. By the way, there is nothing special about parity, i.e., setting the contributions all exactly equal. We can solve for any target risk contribution share. For example, if we want to use Stocks, Bonds, Bitcoin, Ethereum, Litecoin, then literal Risk Parity would be nonsensical because the three crypto-assets would then contribute three-fifths (60%) of the risk. Rather, I like to keep the contributions from the major asset classes equal. So I target the following splits:

**Traditional assets only**, i.e, 50% risk contribution from stocks and bonds**Add the Crypto Index**, and each asset class gets a 1/3 contribution**Add the three individual crypto coins**: then each gets 1/9**Add only the two major coins**, and they both contribute 1/6 of the risk

I display the Risk Parity portfolios in the table below. We start with the well-known result that risk parity in a stock/bond world would necessitate a huge shift to bonds because stocks are so volatile. Adding the crypto assets we’d need about 4.42% to 4.67% of crypto-assets to capture 33.3% of the portfolio risk.

**Min-Vol portfolio.** In the Stock+Bond world, you’ll end up with an 18% Stock and 82% bond portfolio. Adding crypto assets long-only that’s still the same, implying that you wouldn’t touch crypto-assets even if you had access to them. In a long-short world, you’d short the three individual coins but go long the broader crypto index. The net weight of the crypto-assets is just about -1%. In other words, you’d use the strong equity-crypto correlation to hedge out some of your equity risk through a net short-crypto position. Crypto isn’t useful at all in a min-vol world, but who’s really surprised about that one if these coins have a 100% annual volatility, right?!

But what about the folks who are comfortable with higher risk if that means higher expected returns. If you’re still accumulating assets and you can use the Dollar-Cost-Averaging effect, then you can clearly ramp up the risk target and use crypto assets, while walking up the efficient frontier, right? True, but there might be a better way. As I wrote in a post almost 6 years ago, we could take the efficient frontier diagram, identify the Maximum Sharpe Ratio portfolio, and use leverage to expand the efficient frontier to the left. For example, in the base case scenario with the calibrated expected returns, the tangency point is at about 53% bonds and 47% stocks. No crypto assets are used in the maximum Sharpe Ratio portfolio. If we simply extrapolate along this tangency line we can reach points far superior (i.e., lower risk and/or higher return) than any of the efficient frontier using crypto assets. For example, with a 4x leverage (about 212% bonds, 188% stocks, and -300% cash), we’d reach about 13.1% expected return and 32.6% expected risk. Close to the Bitcoin expected return but less than half the risk of Bitcoin. Who needs Bitcoin, then?

In the crypto debate, you often hear the crypto critics warning of the impending doom, while the crypto fans extrapolate the spectacular past returns into the future. Both sides of the argument are “conditionally correct”, i.e. if crypto is all just a bubble, then stay away. And if crypto keeps going up at 100% a year then that’s very attractive. But in today’s post, I wanted to show that cryptocurrencies aren’t that attractive even in the “intermediate case” where you assume that crypto assets have expected returns of “only” around 2x to 3x that of equities. That’s because crypto volatility is simply too high, coupled with a noticeable equity correlation.

The rationale here reminds me of my old post from 2017 (“This fund returned over 100% year-to-date. I’m still not buying it!“) with a similar flavor: an ETF had strong returns, but it still was not worth it. Because the volatility and downside risk, as well as the equity correlation, were complete dealbreakers. (and sure enough, just a few months after publishing the post, the ETF indeed blew up in February 2018, though I’m not necessarily predicting the same for the cryptocurrencies).

So, if you want to mix a few % of Bitcoin into your portfolio, be my guest. But I would not invest in crypto on a large scale. Especially not in retirement when volatility and drawdowns can pose a real headache.

So, take it for what this is: I’m just a personal finance blogger with an opinion and some technical training and tools to test my hypotheses. People may accuse me of being a crypto curmudgeon because I missed out on the great wave up. Maybe that’s true. People have a tendency to justify their past actions and past mistakes. But I hope that even the crypto fans have gotten something out of my work. Use my ramblings as a devil’s advocate argument. Can you convince me and yourself that my analysis is wrong?

*Title picture source: History Channel*

If you’re familiar with my work on Safe Withdrawal Rates, you’ll know that the number one concern for retirees is Sequence of Return Risk. Well, hopefully, this will soon be a thing of the past. I’m now ready to announce the complete “retirement” (pun intended) of my Safe Withdrawal Rate Research because, after years of research and a partnership with some of the most impressive crypto experts, I have finally developed a way to **completely(!) **hedge against Sequence Risk, once and for all.

Introducing the revolutionary, proprietary, trademarked **S**equence-**H**edged **I**nvestment **T**oken Coin. Guaranteed free of Sequence of Return Risk! It’s safe for retirement, it’s safe for accumulating assets. A patented and trademarked revolutionary crypto technology solution to guarantee a risk-free retirement! With tax advantages, too!

Let’s take a look at the details…

Partnering with the math wizards at CalTech’s Madoff School of Applied Computer Science we developed a coin with a** guaranteed, inflation-adjusted return of 4%,** which would ensure a 4% safe withdrawal rate when planning asset preservation or a 5+% safe withdrawal rate if you’re comfortable with at least a partial asset depletion.

To get the word out we got some of the biggest names in the influencer scene out there, like Jake Paul, Soulja Boy, and Lil Yachty who just recently had their wildly successful “SafeMoon” crypto token launch.

**Let’s get the SHIT show started!**

But it gets even better. As we speak, we’re doing research on an even more powerful coin, a “stable+” coin with a **6% guaranteed return.** The even more advanced “loaded” blockchain technology will soon give rise to the **S**equence-**H**edged **I**nvestment **L**oaded **L**edger (SHILL) coin. Also trademarked!

**Let’s get SHILLing, everybody!**

* * *

OK, before I get angry comments and hate mail, this is obviously an April Fool’s prank. I just like to raise awareness of how pervasive crypto scams have become. They often have the same modus operandi, namely a well-known influencer marketing some worthless crypto asset, either a coin or an NFT, and after all the unsuspecting investors plowed in their money, the developers run away with the cash. It’s even easier than the age-old penny stock pump-and-dump because, by construction, the crypto assets are already in the hands of the developers. There is no need to buy an illiquid asset before the “pumping” like in the case of penny stock scams.

What always amazes me is that for relatively little money, internet personalities are willing to jeopardize their reputation. For example…

- Above mentioned Jake Paul, Soulja Boy, and Lil Yachty, are now defendants in a class-action lawsuit over the scammy “SafeMoon” tokens.
- Floyd Mayweather has a history of one pump-and-dump after another. Didn’t he make $300m in his 2017 fight? Did he spend all that money already that he has to raise more cash in this crummy way?
- Kim Kardashian promoted EthereumMax back in May 2021 and was paid a six-figure sum. The coin is now essentially worthless.
- And many more. Check out the Coffeezilla YouTube channel for countless other examples.

So, stay vigilant everybody. The only explicit investment endorsement you’re going to see on my blog today is for FZROX and FNILX, the domestic Fidelity zero-expense-ratio equity index funds.

Also, please check out my prior-year April Fools Day posts:

- 2018: Does Big Ern really exist?
- 2020: The Ultimate Tax Hack: We Are Moving To Monaco!
- 2021: The Entire Safe Withdrawal Rate Series: to be published on TikTok!

Last year in Part 49 of the Safe Withdrawal Series, I wrote a post about using leverage in retirement, and in today’s post, I like to explore some additional issues.

A quick recap, the appeal of using leverage in retirement is that we would borrow against the portfolio instead of liquidating assets. Nice! That might help with Sequence Risk if we avoid liquidating assets at temporarily depressed prices. There could also be a tax advantage in that we keep deferring the realization of taxable capital gains, potentially until we bequeath our assets to our daughter who can then use the “step-up basis” for complete forgiveness of all of our accumulated capital gains. That’s the famous “buy, borrow, die” approach popular with high-net-worth folks.

The gist of the post last year: Not so fast! Leverage could potentially even **exacerbate** Sequence Risk if you are unlucky and retire right before a bad market event that’s deep enough (like the Great Depression) or long enough (like the 1965-1982 stagflation episode) to compromise the portfolio so badly that the margin loan becomes unsustainable relative to the underwater portfolio.

One solution proposed by several readers: instead of **always **borrowing against the portfolio, maybe we should **carefully time when we use leverage. **For example, borrow only when the stock market is down “far enough” and use withdrawals from the portfolio otherwise. And if the market is doing well again, potentially pay back the loan again! Sounds like a reasonable and intuitive plan. But I want to put that to the test with some real simulations. Let’s take a look at the details…

In the post last year, I modeled the margin loan with a **fixed real interest rate.** I realize that a slightly different assumption might be more realistic, namely using a fixed spread over a **short-term government reference rate.** That’s because if you want to borrow on margin, your broker will likely not quote you a rate as “x% over CPI inflation” but, more likely “x% over the Federal Funds Rate (FFR)” or some other short-term rate like the 3-month T-Bill rate or LIBOR. What would be a reasonable assumption for the margin loan spread?

- A Home Equity Line of Credit (HELOC) often has an interest rate tied to the
**Prime Rate**, which is itself about 3 percentage points above the (overnight) Federal Funds Rate (FFR). I remember back in the good-ol’ days you could get HELOCs for Prime minus 0.75%, even 1.00%. But I think today’s rates are closer to Prime +/-0% or maybe minus 0.25% if you have good credit and shop around a bit. So, if you get a HELOC with a rate equal to prime minus 0.25%, you’ll pay around 2.75% above the FFR. - M1 Finance offers rates between 2% and 3.5%. That’s a wide range. It looks like the upper edge is actually inferior to the average HELOC. I couldn’t ascertain what benchmark rate they use, but I’d suspect, the range of interest rates will likely move up in line and 1-for-1 with the Federal Reserve policy rate.
- Interactive Brokers will lend to you at a rate of 1.50% above the FFR for smaller amounts, and 1.00% for medium-sized loans ($100,000-$1,000,000). Loans up to $50,000,000 go for 0.75% above the policy rate. And 0.50% for loans $50m+, if you’re loaded enough. This is all for the IBKR PRO account. The IBKR LITE account charges significantly more.
- Borrowing through a box spread trade as I discussed in my post in December 2021, you might get rates as low as 0.3-0.5% above the T-Bill rates. That’s likely the lowest rate you will encounter anywhere.
*(side note: most likely you’d choose a longer-term loan, maybe 1-2 years. Potentially as long as 5 years. The 0.3-0.5% spread refers to the spread above the T-Bill or Treasury bond of the same maturity, not necessarily the spread above the realized Fed Funds Rate. But over shorter horizons, the T-Bill rate is a pretty accurate prediction for the average FFR over the same time span)*

It turns out that the choice of the loan rate will make quite a difference in the margin loan calculations. For example, last time I used real rates of 0%, 1.5%, and 3% with the middle value of 1.5% above CPI as my “preferred” value. I like to recalculate the scenario for the November 1965 retirement cohort with a $1,000,000 initial portfolio withdrawing $30,000 annually and supplementing the withdrawals with a margin loan worth $10,000 annually. For the CPI+x% loan rate, I use the middle value of 1.5% and contrast that with three different FFR+x% loan scenarios: a 0.50% spread (best possible case: box spread trade), 1.25% spread (margin loan with Interactive Brokers), and 2.75% (HELOC, and other not so attractive brokers). The portfolio value net of the 3% withdrawals is the same in all four scenarios but the loan balances are quite different, see the chart below. It turns out that the FFR+x% loan interest looks far worse in the 1965-1995 time span than I had previously assumed. That’s bad news because it means that the margin issues that hamper our “buy, borrow, die” efforts would have been even more constraining than I previously assumed. Inflation-adjusted short-term rates were much higher during the crazy 70s and early-80s than I previously assumed!

That said, what hurt us in 1965 would have helped the September 1929 retirement cohort! If I redo the exercise with the different margin rates we get the following picture, with far lower loan-to-portfolio ratios when using the FFR+x% rule. That’s obviously because the realized short-term real rates were quite low during the Great Depression.

Let’s get to work and run some simulations. I want to start with the November 1965 cohort because, as the results above show, that seems to be the most constrained cohort and potentially the one with the most to gain from timing the margin loan draws.

Let’s start with the base case simulation, where we use a 4% annualized withdrawal rate, and a quarter of the monthly budget is financed through the margin loan, *every *month. I display the simulation results, for this and all the subsequent scenarios, in this simple chart plotting the **real CPI-adjusted** time series of the portfolio, loan, and net worth balances (left axis) and the monthly margin loan draws (right axis). The monthly budget is $3,333.33 (4% annualized), $2,500 of which comes from withdrawals and the remaining $833.33 from the loan. There is no timing (yet). We confirm again that this would have been at the very least a very unpleasant retirement experience, with the net worth depleted to $133,000 about 17 years into your retirement. The maximum loan-to-portfolio balance would have been 72.3%. That means for every $100 of portfolio value, only $27.70 was your net worth and $72.30 came from the loan. That’s almost a 4x leverage, which would have likely busted your portfolio and caused a forced liquidation by the brokerage, considering that I simulated this only at a monthly frequency, and daily and intra-day fluctuations would have easily pushed you beyond your margin constraints.

Since a 4% withdrawal rate and 25% of consumption financed through the loan wouldn’t have worked in 1965, let’s see how much we have to reduce our budget to make this work. Let’s assume that this retiree wants to keep a $250,000 safety cushion after 30 years. Without any leverage and using a 75/25 portfolio, I compute the baseline safe withdrawal rate as 3.58%.

How about with leverage? I use the built-in Excel Solver function to maximize the retirement budget subject to the $250,000 final net worth target and the 50% upper limit on the loan/portfolio ratio (=2x leverage), by changing the withdrawal rate and the “Borrow%” value, i.e., the share of retirement budget funded by the margin loan. This is still without timing the margin loan, i.e., we withdraw the same (real CPI-adjusted) amount every month. The results are pretty disappointing. Even with an extremely inexpensive margin loan rate, we can only finance about 10.76% of the retirement budget (a little over $300/month). And lift the safe withdrawal rate to 3.78. Better than 3.58%, but still no panacea for sequence risk either!

Let’s look at the following timing mechanism: we fund 100% of our retirement from withdrawals unless the S&P 500 drops to a certain percentage below its most recent all-time high. Let’s start with a 20% drawdown target. We can indeed raise the withdrawal rate and margin loan percentage to 3.84% and 26.48%, respectively. Still a bit shy of the 4% Rule but not bad. Notice how the margin loan draws, about $850/month, occur briefly during the 1970 recession and bear market, the 1973-1982 stagflation era, and again briefly during 1987/88 stock market hiccups. Out of the 360 months of retirement, we’d use the margin loan “only” 125 times. Also notice that we easily spot the time when the margin loan constraint binds: When the blue line touches the green line we’d have loan+net worth=portfolio, and thus loan=0.5*portfolio, i.e., exactly 2x leverage.

If we look at the time series chart of the previous simulation, we notice that the 50% margin ratio hits you relatively late in retirement (month 349), during the 1994/95 Peso Crisis and the resulting stock market weakness. During the ugly 1982 stock market bottom, we had a loan to portfolio ratio of “only” about 32%. One way we might be able to increase both the margin loan use and the safe withdrawal rate would be to pay back the loan during the 80s/90s stock market rally to relax the 50% margin constraint in 1994.

So, let’s assume that if we reach a **fresh all-time high** in the S&P 500 Total Return Index, we’ll start paying back the margin loan. I assume that we simply double the withdrawals from the stock/bond portfolio and use the excess to pay down the margin loan, i.e. set the margin loan draw to -100% of the monthly retirement budget. This method allows us to raise the WR to 3.91% and the margin loan portion of the withdrawals to 41.08%. We still draw the margin loan during 125 months but we also pay back the loan for a few months in 1972, and then again starting in 1985, for a total of 47 months. Notice that the maximum margin constraint is now binding in 1982 again at the bottom of that recession when the margin loan touches the net worth line.

I also played around with more restrictive drawdown constraints, i.e., use the margin loan only when the stock market is down by 25%, 30%, and 35%, respectively. I don’t prepare separate charts, but report the complete simulation results in the table below. Indeed, we can push the safe withdrawal rates even a little bit higher if we move to a 30% cutoff, but at 35% there is a huge deterioration again. Having to wait until the market drops by 35% appears to be too restrictive, at least during the 1970s. But it seems that anything between 20 and 30% seems like a neat option. The no-leverage withdrawal rate would have been only 3.58% and we can improve that by about 33-36bps, or about 9-10%. Not bad at all!

Also, to explain again how the numbers were created: with the exception of the first column, where I just calibrate the WR and the Borrow% at 4% and 25% (and we clearly get way too much leverage), I use the Excel Solver function to maximize the retirement budget subject to the $250,000 final net worth and the 50% upper limit on the loan/portfolio ratio (=2x leverage), by changing the withdrawal rate and the “Borrow%” value, i.e., the share of retirement budget funded by the margin loan.

I also included a reader suggestion in the last column on the right, where the loan draw vs. payback is timed not by the S&P 500 drawdown, but by what I call a** “Portfolio on Track” **indicator. I check if the projected portfolio value net of withdrawals, assuming a 4% real return rate. And then subtract the current margin loan balances with interest. If you’re below the final bequest target of $250,000, draw down the loan, if you’re on track then withdraw the retirement from the portfolio and – if applicable – pay back the loan as well. I haven’t played around very much with this rule, and maybe it can be optimized some more, but the equity index drawdown rule appears to be superior for the 1965 cohort.

As always, there are a few warnings and caveats to keep in mind here:

- There is no way an actual retiree in 1965 would have been able to borrow at a rate of FFR+0.50%. We’d have to view my calculations here as a “thought experiment” of whether with today’s financial innovations – index funds, low expense ratios, low margin rates – we can use leverage and still survive a repeat of the return patterns of a historical worst-case scenario!
- If your margin interest is higher, say FFR+1.25% (IB margin loan) or FFR+2.75% (HELOC), some of the appeal of the margin strategy evaporates. The withdrawal rates for the 25% drawdown timing mechanism go from 3.92% to 3.87% and 3.75% when raising the loan spread rate from 0.5% to 1.25% and then to 2.75%, respectively.
- If you indeed plan to use the box spread trades, keep in mind that those loans tend to be “lumpy”. I initiated three box spread loans so far, one with a 200-point spread and two with a 1,000-point spread, worth $20,000 and $100,000, respectively. Rather than doing a box trade every month, most people would likely to draw down the IB margin loan at a slightly higher interest rate until they reach a large enough loan balance and then initiate a new box spread loan, in the low-to-mid 5-figures.
- Also, keep in mind that most actual retirees face an even tighter margin constraint than what I model here because only traditional brokerage accounts allow margin loans. You can’t do this in a retirement account!

Just for completeness, let’s redo the same exercise for the September 1929 cohort, right at the stock market peak before the Great Depression. The unleveraged safe withdrawal rate was 3.61% in this cohort. Quite intriguingly, the margin loan would have provided a tremendous improvement in the safe withdrawal rates. The base case with the 4% WR and 25% borrow share would have stayed way below the 50% margin constraint. So, even without timing the margin, you could have gone to a 4.39% withdrawal rate and financed 31.86% of your expenses with the loan. And it gets better when you time the loan draw and the repayment. With a 35% drawdown criterion, a 4.93% withdrawal rate would have been feasible.

There is no panacea against Sequence Risk. I didn’t expect this to be one either. But I was positively surprised that a small dose of leverage can indeed smooth out **some **of the headaches of even the historical worst-case retirement scenarios.

A negative surprise: even if you use the margin loan very occasionally, i.e., only after a stock market drop of 25% or more, it would still be too risky to fund all of your retirement expenses with a margin loan. I would use the loan only very sparingly, to replace only about 50% of the retirement budget, even after a 25% drop! Applying this rule to the more recent retirement cohorts, you wouldn’t have utilized the margin loan even during the 2020 bear market because the **month-end** drawdown in March 2020 would have been just under 20%. Even though the February 19 to March 23, 2020 drawdown was almost 34%! Under the leverage timing rules studied here, you would use leverage only during the 2002-2003 or 2007-2009-style market meltdowns, not the garden-variety volatility we’ve seen post-2009.

I am also surprised about the margin loan working so well in the 1929 case study. I would have expected the reverse, i.e., I thought that the margin loan would have worked better during the 1970s/80s stagflation than during the deflationary 1930s. But of course, the inflation rate alone doesn’t matter so much. **Real **interest rates were painfully high during the 1970s but relatively benign in the 1930s.

But make no mistake, leverage doesn’t work as well as some hand-waving “experts” on the interweb want it to appear. We can’t* “just use the margin loan”* and all worries about sequence risk go away. The historical worst-case scenario retirement starting in 1965 needed to tread much more carefully. Don’t even think about using the margin loan to fund your entire retirement. That’s only for the ultra-rich with a nine-figure+ net worth and a 1% withdrawal rate. But, again: using leverage sparingly, say, 40-50% of the retirement budget is funded through a loan and only when the stock market is down significantly, we can make a noticeable dent in the effect of Sequence Risk.

PS: For the math wonks, I posted the Excel Sheet here. This is not a sheet that would work well with Google Sheets due to Google’s inferior solver function. So, it’s an “*.xlsx” file. Since I never intended to share it, it might take a bit of a learning curve to figure things out. It doesn’t have enough documentation to serve as an easy plug-and-play toolbox.

*Title picture credit: pixabay.com*

What a difference a year makes! In late 2020, only about 16 months ago, I felt the urge to comment on the then-fashionable discussion of how **low inflation** would impact retirees. See Part 41 – Can we raise our Safe Withdrawal Rate when inflation is low? of my SWR Series. Feels like a lifetime ago, doesn’t it?

The takeaway back then: don’t get distracted by high-frequency economic fluctuations. Low inflation doesn’t necessarily mean we can all raise our safe withdrawal rates. Certainly not one-for-one. There is neither empirical nor theoretical economic backing for materially changing your retirement strategy.

Only a little more than a year later the tide has turned. We’re now facing the highest inflation readings in about 40 years. 7.5% CPI and potentially 8% year-over-year once the BLS releases the February figure in mid-March. So, people asked me if my inflation views are symmetric, i.e., high inflation is also a non-event? As I signaled in my inflation post last month, I’m not too worried. Here’s why…

Before we begin… a favor to ask: Please check out my recent podcast appearance on the White Coat Investor. It’s also available on YouTube. Talking about Safe Withdrawal Rates, Robo Advisers, Target Date Funds, Annuities, Trading Options, and more.

Today, I want to perform a type of analysis that had been on my mind for some time but I waited for the right occasion to talk about it: I have extensive time-series data on safe withdrawal rates and a bunch of macroeconomic and financial observables, like the CAPE Ratio, 10-year bond yields, inflation number, etc. The economist/econometrician/statistician in me would scream: “that calls for running a regression to determine how different macro/finance fundamentals impact your safe withdrawal rate!” Essentially, estimate an equation of the shape

SWR = a + b1*StockEarningsYield + b2*Bond Yield + b3*ShortTerm Yield + b4*CPI + etc.

Why did it take me so long to perform this analysis? Well, to be honest, there are a few “snags” in this type of analysis that make it mostly an interesting **academic exercise**, but maybe a little less useful as a **practical tool **for an early retiree “in the trenches” trying to pin down a withdrawal rate. More on that later. But I still believe that this type of analysis can educate us how – at the margin – higher or lower inflation would impact the safe withdrawal rate derived from my Safe Withdrawal Rate Toolkit.

For the safe withdrawal rates, I generate twelve different series with my Google Sheet Toolkit:

- 3 different Stock/Bond allocations: 60%/40%, 75%/25%, 100%/0% Stocks/Bonds
- 4 different assumptions on the length of retirement and the final portfolio target:
- 30 years horizon, FV=100% of the portfolio (capital preservation, after accounting for inflation)
- 30 years horizon, FV=25% of the portfolio, i.e., only partial capital preservation, say because
- 30 years horizon, FV=0% (capital depletion)
- 50 years horizon, FV=0% (capital depletion)

I will use each one of the 3*4=12 combinations (one at a time!) as the dependent variable.

For the explanatory variables (=independent variables), I use the following eight series:

- The Shiller CAPE earnings yield, i.e., the inverse of the CAPE ratio, at the beginning of retirement
- The 10-year benchmark bond yield at the beginning of retirement
- The short-term yield (e.g. 3-month T-Bill) at the beginning of retirement
- The 1-year CPI inflation (i.e., rolling over the past 12 months)
- The 1-year
**future**CPI inflation - The 5-year
**future**CPI inflation - The 10-year
**future**CPI inflation - The 30-year
**future**CPI inflation

Notice that only regressors 1-4 would have been observable and available at the start of retirement (subject to a small caveat because the CPI comes out a few days after the month-end). But, again as an academic exercise, I can certainly include **future **realized inflation to see how a retiree would have changed his/her withdrawal rate if he/she had indeed had the perfect foresight and had known the future realized inflation rates.

Some more technical notes:

- I run the regressions from 01/1920 to 12/1991, at a monthly frequency. Thus the last retirement cohort is the final cohort that had 30 full calendar years of actual portfolio returns.
- The 50-year retirement horizons would include up to 20 years of calibrated/estimated return data toward the end. Thus, we want to use those results with a grain of salt. But, then again, as I pointed out in Part 14 and Part 15, due to Sequence Risk, the portfolio returns during the latter part of retirement have relatively little impact on the SWR.
- All regressions use the Matlab/Octave package “nwest” to calculate the Newey-West heteroscedasticty-adjusted t-statistics. Simple Ordinary Least Squares (OLS) slope estimates are indeed correct, but the t-statistics would have been overstated due to the overlapping windows!

As a warm-up, let’s look at the **univariate **regression results (y = a + b*x) of one specific SWR Series: 75%/25% portfolio, 30-year horizon, and 25% final value target. I use this set of “favorite” model assumptions often because it’s a great baseline for both early and traditional retirees. It works for a traditional retiree with a 30-year horizon who wants to leave a quarter of the portfolio as a bequest. Or an early retiree who wants to bridge 30 years until Social Security and Pensions set in and keep the 25% final value target to supplement those cash flows later in retirement.

Let’s look at the scatter plots of the independent variable (x-axis) and the safe withdrawal rates (y-axis). I group these into 4 charts with scatter plots each. Let’s start with the stock earnings yields and the 10-year bond yields, see below:

- The Shiller earnings yield has a strongly significant slope parameter (β=0.55, t=4.98) and a very impressive correlation of ρ=0.84. All the failures of the 4% Rule happen when the CAEY is below 5%, i.e., when the Shiller CAPE is above 20. Regular readers will know that I’ve been “preaching” that since 2016!
- The intermediate-term bond yield also has a positive impact on the SWR, but the relationship is certainly not linear. And it’s not even monotone either! For very low bond yields, historical SWRs were elevated again. The sub-4% withdrawal rate all occur in the “middle region” between 3% and 6.5%.
- By the way, regular readers will recognize the two charts (though updated with newer data) as part of my analysis debunking troll-extraordinaire Financial Sumoguy’s claim that we need to pin our withdrawal rate to the 10-year yield, and the 10-year yield
**alone**: “Do we really have to lower our Safe Withdrawal Rate to 0.5% now?” (August 31, 2020). The lesson back then: That’s really dumb. The 10-year yield is not very useful when determining a safe withdrawal rate of the average Stock/Bond portfolio.**Equity valuations matter most!**

Moving on to short-term yields and inflation:

- Short-term yields (3-month T-bill) indeed correlate a little bit with the current SWR. The t-stat is 1.9 which would qualify as significant at the 5% level for a one-sided test. But also notice that all of the failures of the 4% Rule occur between 3% and 7% short-term yield, not really when yields are low. You’re looking at a range of the blue cluster of +/- 4 percentage points around the red line. As a standalone regression to learn about SWRs, this is utterly useless. But this regressor might be useful in the multivariate regressions below.
- If we try to relate the trailing inflation rate with the current SWR, not only is the relationship statistically insignificant (t=1.30). The very small slope actually goes in the wrong direction: a
**positive(!)**relationship between past inflation and future SWRs. That flies in the face of all those running around in panic in light of the high CPI numbers now.

Next, let’s look at how the benefit of perfect foresight about future inflation could have “predicted” the SWR. Let’s start with the first chart and look at the 1-year and 5-year annualized CPI rate on the x-axis and the SWR on the y-axis. There’s pretty much no relationship. It doesn’t take an economics Ph.D. to figure that one out! So, quite amazingly, future inflation over a short-to-medium horizon seems uncorrelated with future SWRs.

And, finally, the 10-year and 30-year future realized inflation (annually):

- The 10-year realized inflation rate has a negative slope, but it’s only about -0.20. But the negative slope is statistically significant (t=-2.21). But again, there’s a huge band of blue dots around the red line. On a standalone basis, even knowing the future 10-year inflation rate is useless!
- The 30-year future realized inflation rate has the best statistical association with the current SWR. That’s pretty impressive: a slope of about -0.94 (so, indeed, the realized inflation rate reduces your SWR almost one-for-one!). The slope parameter is highly significant (Newey-West t-stat of -2.75) and the correlation is also not too shabby. But notice one fly in the ointment? Between 1929 and 1959 we had modest inflation, just under 2%, and that’s when the 4% Rule failed. So, 30 -year realized inflation rates are not very useful when pinning down SWR on a standalone basis.

Equity valuations matter the most. And recall, the CAEY is something that’s actually **observable **at the start of retirement. Trailing inflation has a **positive (!) **impact on the SWR and even with the perfect foresight of the future 30 years of inflation you can only hope for a whacky, not exactly monotone relationship between inflation and the safe withdrawal rate.

Hence, my assessment of the current macro and financial conditions: we should certainly be worried about the future and choose a conservative safe withdrawal rate. But that has nothing to do with inflation, and has **everything **to do with lofty equity valuations!

One other exercise before we jump into the multivariate regressions (i.e., multiple explanatory variables at the same time). Let’s look a the univariate regression results of regressing all the 12 different SWR series on the Shiller CAPE yield. Please see the table below.

- I marked the 75/25, 30Y horizon, 25% FV target because we will use this SWR series in more detail later.
- All slopes and intercepts are highly statisitcally significant.
- Quite intriguingly, the slope estimate for the CAPE yield is always just about 0.5. If you ever wonder why the CAPE-based safe withdrawal rate rules (see Part 18) work so beautifully with a slope parameter of 0.5, this is the reason!
- Of course, if the equity portion is all the way at 100%, then you ‘d increase the importance and thus the slope of equity valuations. Makes perfect sense, too!
- Playing around with different horizons of final value targets for a given asset allocation, mainly impacts the intercept, not the slope. For example, in the 75/25 example, you’d use a 1.61% intercept and 0.541 slope with capital preservation. But if you want to deplete your portfolio you’d keep roughly the same slope (0.557) and shift up the intercept to 2.73%.

By the way, what kind of SWR would be recommended from the above regressions using today’s CAPE yield? If we assume a CAPE of around 35 as of 2/25/2022, then the 75/25-30Y-25%FV regression would imply a safe withdrawal rate of 2.45% + 0.553/35=4.03%. Whoa, that’s awesome! The 4% Rule works, even in today’s environment? Well, not so fast! Remember that the good-old regression draws a line **through the center** of the scatter plot, trying to minimize a squared-deviations loss function. With a 4% withdrawal rate, we’d then risk a failure rate of 50%, gasp! And the spread of the blue dots around the red line is huge, with a standard deviation of 1.12% for this model. We might need to reduce that SWR quite substantially, to lower that probability of failure. We can gauge from the scatter plot that we’d need to shift down the red trend line by probably roughly 1.25 percentage points to capture the **lower edge** of the scatter plot. 2.88%! That doesn’t sound so hot anymore!

Since the different SWR assumptions mainly impact the intercept, not so much the slope, let’s fix one specific SWR time series, i.e., our good-old 75/25 portfolio 30-year horizon, 25% final value target, and study how multiple regressors would jointly account for the safe withdrawal rate variations. I propose 8 different regression models

- Baseline univariate regression with the CAPE yield only
- Add the 10-year bond yield
- Add the short-term yield
- Add the 1-year trailing inflation
- Add the (perfect foresight) 1-year future inflation
- Instead of the 1-year, use the 5-year future inflation rate
- Instead of the 5-year, use the 10-year future inflation rate
- Instead of the 10-year, use the 30-year future inflation rate

In the table below are the regression results:

Going through the regression results as we add and change regressors, here are a few intriguing results for the 8 different models:

- Model 1 is again the baseline univariate model. Not much new here. The R^2 of the regression is 0.707.
- Adding nominal 10Y bond yields, we get a slightly positive but not significant slope. Not a shocking result;
*nominal*bond yields don’t matter much for*real*SWRs. - Adding short-term yields we now make both fixed income slopes significant, and of opposite sign. That’s very intuitive! Nominal bond yields don’t matter much, but the slope of the yield curve does. The R^2 is improved somewhat. But, again, notice that 70% of the SWR variance is already captured through the CAPE yield. Only an additional 0.07 come from the yield curve!
- Adding the trailing inflation adds nothing! The slope is negligible (0.005, much lower than the 0.07 in the univariate regression). The R^2 is unchanged.
- Adding the 1-year forward realized CPI also doesn’t add much.
- If we use the 5-year forward inflation rate instead, we indeed get a little bit of extra R^2, now at 0.818. And the slope of the 1-year trailing CPI is positive (albeit not exactly significant) while the future inflation gets a negative beta. That makes sense! The
**level**of inflation is not that crucial. It’s more the**direction**! In other words,**moderating inflation is actually beneficial for the SWR!**Which bodes well for out current situation, because I can’t see how inflation will move much above 7.5% and certainly not for an extended period. - If we replace the 5-year forward CPI with the 10-year forward figure, we get the highest R^2 overall. All slope estimates are significant now of 5 years or even 10 years!
- Quite intriguingly, if we knew the entire 30-year future inflation average, we lower the R^2 again relative to knowing only the first 10 years. And the t-stat on the 1-year trailing CPI deteriorates somewhat. It’s an intuitive result again; due to Sequence Risk, it’s actually the first ten years of your retirement that decide about success vs. failure, not so much the entire history.

Let’s look at the results from Models M6, M7, and M8, i.e., the regressions with the highest R^2 and the most significant t-stats for all the regressors. What happens if we were to plug in today’s observables for the stock earnings, bond yields and trailing inflation, as well as some inflation forecasts? Notice that we know from above that the absolute numbers may not be that useful because the regression line goes *through *the data cluster and will likely create more of a mid-point SWR with a 50% failure rate, not so much a failsafe withdrawal rate. But the changes in SWR give us an idea about how – purely at the margin – changing some inputs will change the SWRs.

For the CAPE, I use an estimate of 35.05 as of the 2/25/2022 close. The bond yields are from Bloomberg.com and even though I pulled the numbers on 2/25, they seem to be the 2/24 closing quotes. But close enough for government work. The 1-year CPI estimate (not used in M6/M7/M8, but just displayed for fun) is the Michigan Survey 1-year ahead CPI estimate. The 5, 10, and 30-year CPI estimates are the TIPS-implied rates, also from Bloomberg, also for the 2/24 close.

Here are the results: First, start with a Goldilocks economy: Not too hot, not too cold. A CAPE of 20, i.e., an earnings yield of 5%. 4% yield for 10Y, 3% for short-term. And inflation at a steady 2%. The 3 different regressions give you an initial SWR of between 5.12% and 5.97%. Knock off another 1.25% to get to a failsafe estimate and that’s a nice generous initial withdrawal rate!

Next, keeping all the bond and inflation inputs the same, let’s change *only *the CAPE to 35.05 and thus the CAEY to 2.85%. Bummer! the SWR drops by between 99 and 118bps. That may not sound like much, but that could be a quarter or a third of your retirement budget!

Third, if we also adjust the bond rates and inflation numbers to match today’s environment, we change the SWR by about…, uhm, nothing. In fact, the model estimates **go up** by a few bps. Not really anything to write home about either, but contrary to popular belief, our current inflation landscape has essentially no bearing on the SWR.

And again, I’m not saying we should ignore macro fundamentals. We should pay close attention to the one macro fundamental that matters, equity valuations. But everything else is a rounding error in your SWR! Sometimes you get *statistically *significant parameter estimates. But if you play with inputs the results are not really *economically *significant.

That’s not to say that inflation is totally irrelevant. If our current TIPS-implied estimates are wrong and I plug in the historical **worst-case** numbers for 5/10/30 years we certainly get that SWR moving. Down by another 103-155bps. Tighten your belt by another 26-35%, just based on inflation. But I have trouble justifying 8.84% inflation for another 10 years. Unless we have a replay of the 1972-1982 inflation runup.

For the 75/25 portfolio, 30-year horizon, and 25% final value target, we observe the lowest SWR in the mid-1960s. November 1965, to be precise. This means the retiree used the 10/31/1965 observables and starts withdrawing on that date for a Nov 1 retirement. Plugging in the 10/31/1965 CAEY, fixed income, and CPI data, we get a regression-predicted SWR of 3.79%, please see the table below. That’s not too far away from the actual 3.58% SWR. Let’s plug in today’s observables and attribute the **changes** in the overall SWR (+0.63%) to the different components:

- The S&P500 is significantly more expensive today, as measured by the CAPE. All else equal, that would account for a 64bps lower SWR.
- The yield curve is much steeper, which gives you slightly positive net impact on the SWR: -165bps + 189bps = +24bps
- The inflation shock 1965->1975 was much worse than what’s predicted for us today. The realized CPI inflation 5.66% was much worse that what the bond market predicts right now and the shock relative to past inflation (only 1.7%) was also much worse. That’s a +102bps impact on the SWR.
- All of the “marginal” impacts sum up to a 63bps
over the 1965 worst-case scenario. This would imply a 4.41% SWR from the regression or a 4.21% SWR if we add the 63bps to the actual 3.58% fail-safe.**improvement**

Of course, the calculations look a lot worse if we apply the post-1920 historical worst-case inflation rate of 8.84%. With that input, we reduce the SWR by 92bps. That gets you to 2.86% if simply plugging into the regression equation or 3.58%-0.92%=2.66% if we apply the marginal adjustments to the actual 11/1965 SWR. That’s a painfully low withdrawal rate.

And the last thought experiment: How bad would inflation have to be over the next 10 years to match the same SWR, i.e., the historical failsafe WR? That’s in the table below. Even with a 5.10% CPI rate over the entire next 10 years, we’d still get an SWR only as bad as the historically worst SWR in 1965. I find it hard to believe that we’ll see a CPI realized rate that high and even if we do, we move the SWR “only” back to the historical failsafe.

Looking back at historical data, the previous worst-case scenarios for retirees, either the 1929 cohort or those around 1965-1968 generated some pretty conservative safe withdrawal rates. Certainly below 4% but not really that much below 4%. What’s currently predicted for the inflation path is all well within historical norms, thus, a failsafe calibrated to historical data should easily hold up in the future. I don’t see a reason to throw in the towel and change anything in my methodology.

Expensive equities are the gorilla in the room. It’s certainly possible that the Federal Reserve in an inflation-fighting mood could trigger a large sell-off, like in 1982. But again, that episode is already part of my simulation toolbox. Unless the inflation shock is much worse than in the 70s and 80s, I’m still sticking with my methodology. If that ever changes, I’ll write about it here!

*Title picture source: pixabay.com*

According to the most recent inflation numbers that came out yesterday (1/13), CPI inflation is now running at 7% year-over-year. From September to December we saw a 2.2% increase, which is a 9.1% annualized rate. And it’s not all energy and food inflation. The core CPI is also elevated at 5.5% year-over-year.

What do I make of this? How persistent or transitory is this inflation bump? Should we adjust our portfolio? Or our safe withdrawal rate? Here’s a short note with my thoughts…

Before we get started, though, please make sure you check out my recent podcast appearance on “Hack Your Wealth” where I talked about inflation as well as other issues like equity valuations, floating-rate preferred shares, and crypto investing:

How current economic changes impact retirement safe withdrawal rates (via Youtube)

For the longest time, people have been telling us not to worry about inflation because it’s just **transitory.** Well, if someone tells me inflation is transitory and they **keep **telling me that every month and every quarter and every year, it eventually gets old. Late in 2021, FOMC Chairman Jerome Powell finally conceded that “it’s probably a good time to retire that word [transitory].” Note that this doesn’t mean that 7% is now going to be **permanent**. It simply means that the inflation shock will likely be more **persistent **than anyone had predicted, but at least for now, the working assumption is that in the long-term, we’ll see more contained inflation again. And the hearing in early December where this came up served as a heads-up to everyone that at the December meeting, the FOMC will project a slightly more aggressive interest rate path than before.

In other words, will I get to see normal inflation again in my lifetime – to counter the classic “In the long-run, we’re all dead” issue raised by an old (now-dead) economist? Let’s check what the accumulated wisdom and prediction power of financial markets have priced in. TIPS-implied inflation rates are the spread between nominal Treasury bonds and the (real) TIPS yield, i.e., what TIPS owners will get paid over and on top of inflation. There are some problems when using this measure, of course. Notably, during market stress periods you might get “iffy” estimates because TIPS are not as liquid as Treasuries. But right now, I don’t think this objection applies.

As of January 13, here are the Yields and the implied CPI rates, all annualized, see the table below. Yes, the 5-year CPI estimate is elevated, at 2.8%. The 10-year rate is already down to 2.5%. And if we “back out” the TIPS-implied inflation rate for the years 6-10 as [1.0249^10/1.0282^5]^(1/5)-1, we get an implied inflation rate of 2.16%, not significantly different from everybody’s long-term 2% estimate. Indeed, the Federal Reserve uses the Core-PCE as their preferred inflation measure and that’s usually a bit below the CPI, this brings us right back to where we need to be!

Also, notice that this 2.16% figure for the medium-to-long-term inflation pressure is not at all outside of historical norms. If we plot the time series of TIPS-Implied CPI since 2003, we notice that 2.16 for 6-10 years ahead is below the historical average (2.25%) and certainly below some of the historical peaks (3+%). It’s about in the same ballpark as in 2018. So, if you wonder why financial markets are not yet panicking, this is it: Past inflation is “water under the bridge” and the outlook isn’t so bad.

But is this sanguine inflation picture even realistic considering the recent 7% YoY numbers? How quickly (or how slowly) do we have to move back to that 2.16% long-term figure and still be in line with the TIPS-implied measures? Glad you asked because I did some simple Excel calculations to check that. I looked at the most recent inflation figures and noted the 0.47% month-month CPI (almost 6% annualized). Let’s assume that over the next 10 years, the monthly CPI advances converge back to that 2.16% long-term target and they do so with a “half-life” of a specific number of months. I played around with different half-life parameters, and at 8 months we get future 5-year and 10-year predicted inflation numbers exactly aligned with the TIPS-implied numbers (well, within less a 0.01%, at least), see the chart below.

What’s astonishing is that even though we slowly walk the monthly inflation numbers back to the long-term target, the year-over-year measure is bound to go up for two more months and is likely to peak at 7.4% in February of 2022. That’s because we’re still rolling out the relatively benign CPI numbers in early 2021. Only later when the 8%+ annualized monthly CPI numbers from the Spring of 2021 drop off the YoY calculations would we see a decline. And a very slow one!

In other words, even in this optimistic scenario where inflation pressures slowly abate, the year-over-year numbers will get worse before they get better. And it’s going to take until 2024 for the YoY numbers to drop below 3%. The good news in all of this is that even with CPI numbers looking really rotten for quite a while, it’s still totally consistent with a relatively sanguine inflation outlook over the medium-to-long term, i.e., 5-year and 10-year TIPS-implied inflation estimates.

As you all know, I’m an economist. I eat, sleep and breathe economics. And folks like me sometimes tend to annoy everyone else and pressure people into getting excited about the most recent economic trend (fad?). On inflation, I take the opposite view. We shouldn’t overreact in either direction. I’m reminded of that Bill Bengen paper circulating in late 2020, proclaiming that due to the low inflation rate at that time, we could all increase our safe withdrawal rate to 5%, even 5.5%. That didn’t age well. But even back then, I found this ludicrous and I took some of his claims to the woodchipper in “Can we raise our Safe Withdrawal Rate when inflation is low?” as part of my Safe Withdrawal Rate Series. The same goes for higher inflation: I’ll do what I’ve always done: I point to the risk of high equity valuations (much scarier than inflation!) and the potential of a bad sequence risk event. I would recommend people calibrate their safe withdrawal rates to hedge against some of the historical worst-case scenarios.

Of course, while I’m proposing we don’t do anything *fundamentally *different, we can certainly tweak a few of the details. The prospect of inflation certainly warrants revisiting your safe asset allocation, likely somewhere around 25% of the portfolio. Some people want to argue that due to the prospect of rising rates, it would be safer to shift out of longer-duration bonds and into short-term instruments. Well, not really: the future inflation and rate hikes and yield increases are already baked in. So, unless you worry about inflation and Fed rate hikes coming in *worse *than what is currently predicted, it’s already too late to make that shift. But I grant you that: if you believe that the Fed will raise rates faster than currently predicted, i.e., more than 150bps by the end of 2023, you should consider shortening your bond portfolio duration.

Another idea would be to use floating-rate instruments or fixed-to-floating rate preferred shares, as I do in part of my portfolio. Specifically, I hold a part of my margin cash in my options trading strategy in those floating rate shares, tied to the LIBOR rate. I won’t go into the details too much, but in the Hack Your Wealth Podcast I talk about that at about the 42:30 mark. I should also note that Preferred shares are significantly riskier than government bonds, so there is no free lunch, as I pointed out in Part 29, Part 30 and Part 31 of my SWR Series: Preferred shares have a significantly positive stock market correlation, they should never serve a one-for-one substitute for safe assets. But as a hedge against a nasty interest rate hike, they certainly work. Another plus is that most preferreds are issued by financial corporations whose business model often benefits from higher interest rates (ceteris paribus, at least!).

Just in case, I don’t want people to believe that I’m a Federal Reserve Cheerleader. There are certainly a few worries on my mind. They are all related to this saying/meme that many of you have probably seen or heard in one variation or another:

1: Weak men create hard times.2:

Hard times create strong men.3:

Strong men create good times.4:

Good times create weak men.… and back to 1.

And I should stress that the quote is decades old and referred to **men **and in today’s world we’d probably keep that more gender-neutral. But you get the message, I hope. There are many examples of this natural cycle of building something valuable, and then complacency sets in and you squander what you built. Sometimes people go through cycles like this, sometimes corporations, even entire societies and countries. And this concept surely works for monetary policy as well. Because it, too, often goes through those 4 phases of building and squandering reputational capital:

1:A weak central bank creates out of control inflation.2:

Out of control inflation creates a hawkish central bank.3:

A hawkish central bank brings inflationexpections back under contral.4:

Anchored inflation expectations create a weak and complacent central bank.… and back to 1

For example, we were in phase 1 under Burns and Miller. Then Paul Volcker (phase 2+3) reined in inflation and every FOMC chairman/chairwoman since then has enjoyed the benefits of that strong reputation. Inflation expectations have been anchored thanks to that. Certainly, they still appear to be, as evidenced by the low long-term TIPS-implied inflation expectations. But it makes me wonder: With the easy monetary policy that started potentially as early as Greenspan post-2000 and certainly under Bernanke post-2008, have we already entered phase 4? Will phase 1 be around the corner soon? It’s too early to tell. I certainly hope we’ll navigate those uncertain times and not squander the decades-long reputation of a central bank that cares about price stability.

There was also a brilliant op-ed in the Wall Street Journal by Thomas Sargent, NYU professor and 2011 Economics Nobel Laureate (who I’ve had the honor to meet and talk to several times during my academic career), and he and his co-author make similar points: 1) rebuilding a central bank’s reputation is a *lengthy *and often *painful *process and 2) financial market estimates can be wildly off around the central bank reputation turning points. Just like me, they don’t *forecast *bad things to happen, they merely *worry about the prospect *and want to raise awareness.

So far, I’m not losing sleep over the inflation numbers. No need to run for the hills. This is all still consistent with an economy that was shut down for an extended period and the eventual reopening caused some snags and supply issues. And reckless fiscal policy, which is also bound to end soon! But not all is looking rosy. I certainly cross my fingers and hope that inflation slowly subsides. Right now, financial markets firmly believe that the inflation spike is temporary. But if incoming data points don’t support that view, market conditions will change. As the old saying goes “You can fool all the people some of the time and some of the people all the time, but you cannot fool all the people all the time.” But then again, even if we find ourselves in an inflation spiral like the 1970s and early 80s, I should be safe because my withdrawal strategy would have survived that historical period as well.

*Title picture credit: pixabay.com*